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Geometry-aware Compensation Scheme for Morphing Drones | https://ieeexplore.ieee.org/document/9561774/ | [
"Amedeo Fabris",
"Kevin Kleber",
"Davide Falanga",
"Davide Scaramuzza",
"Amedeo Fabris",
"Kevin Kleber",
"Davide Falanga",
"Davide Scaramuzza"
] | Recent studies have shown that enabling drones to change their morphology in flight can significantly increase their versatility in different tasks. In this paper, we investigate the aerodynamic effects caused by the partial overlap between the propellers and the main body of a morphing quadrotor during flight. We experimentally characterize such effects and design a morphology-aware control schem... |
SplatPlanner: Efficient Autonomous Exploration via Permutohedral Frontier Filtering | https://ieeexplore.ieee.org/document/9560896/ | [
"Anthony Brunel",
"Amine Bourki",
"Cédric Demonceaux",
"Olivier Strauss",
"Anthony Brunel",
"Amine Bourki",
"Cédric Demonceaux",
"Olivier Strauss"
] | We address the problem of autonomous exploration of unknown environments using a Micro Aerial Vehicle (MAV) equipped with an active depth sensor. As such, the task consists in mapping the gradually discovered environment while planning the envisioned trajectories in real-time, using on-board computation only. To do so, we present SplatPlanner, an end-to-end autonomous planner that is based on a no... |
Fast Sampling-based Next-Best-View Exploration Algorithm for a MAV | https://ieeexplore.ieee.org/document/9562107/ | [
"Victor Massagué Respall",
"Dmitry Devitt",
"Roman Fedorenko",
"Alexandr Klimchik",
"Victor Massagué Respall",
"Dmitry Devitt",
"Roman Fedorenko",
"Alexandr Klimchik"
] | In this work, we present a new exploration algorithm for Micro Aerial Vehicles (MAVs). The planner uses a combination of Next-Best-View (NBV) sampling and frontier-based approaches to reduce the impact of finding unexplored areas in large scenarios. For each sampled point, the yaw angle is optimized to maximize the potential gain for mapping. The gain is expressed as a ratio between the exploratio... |
Neuromorphic control for optic-flow-based landing of MAVs using the Loihi processor | https://ieeexplore.ieee.org/document/9560937/ | [
"Julien Dupeyroux",
"Jesse J. Hagenaars",
"Federico Paredes-Vallés",
"Guido C. H. E. de Croon",
"Julien Dupeyroux",
"Jesse J. Hagenaars",
"Federico Paredes-Vallés",
"Guido C. H. E. de Croon"
] | Neuromorphic processors like Loihi offer a promising alternative to conventional computing modules for endowing constrained systems like micro air vehicles (MAVs) with robust, efficient and autonomous skills such as take-off and landing, obstacle avoidance, and pursuit. However, a major challenge for using such processors on robotic platforms is the reality gap between simulation and the real worl... |
Event-driven Vision and Control for UAVs on a Neuromorphic Chip | https://ieeexplore.ieee.org/document/9560881/ | [
"Antonio Vitale",
"Alpha Renner",
"Celine Nauer",
"Davide Scaramuzza",
"Yulia Sandamirskaya",
"Antonio Vitale",
"Alpha Renner",
"Celine Nauer",
"Davide Scaramuzza",
"Yulia Sandamirskaya"
] | Event-based vision sensors achieve up to three orders of magnitude better speed vs. power consumption trade off in high-speed control of UAVs compared to conventional image sensors. Event-based cameras produce a sparse stream of events that can be processed more efficiently and with a lower latency than images, enabling ultra-fast vision-driven control. Here, we explore how an event-based vision a... |
Deep Neuromorphic Controller with Dynamic Topology for Aerial Robots | https://ieeexplore.ieee.org/document/9561729/ | [
"Basaran Bahadir Kocer",
"Mohamad Abdul Hady",
"Harikumar Kandath",
"Mahardhika Pratama",
"Mirko Kovac",
"Basaran Bahadir Kocer",
"Mohamad Abdul Hady",
"Harikumar Kandath",
"Mahardhika Pratama",
"Mirko Kovac"
] | Current aerial robots are increasingly adaptive; they can morph to enable operation in changing conditions to complete diverse missions. Each mission may require the robot to conduct a different task. A conventional learning approach can handle these variations when the system is trained for similar tasks in a representative environment. However, it may result in overfitting to the new data stream... |
A Variable Soft Finger Exoskeleton for Quantifying Fatigue-induced Mechanical Impedance | https://ieeexplore.ieee.org/document/9562118/ | [
"Xiaofeng Xiong",
"Poramate Manoonpong",
"Xiaofeng Xiong",
"Poramate Manoonpong"
] | Interactive (mechanical) impedance and finger fatigues are important topics, which have not been well investigated. To tackle this problem, we developed a soft lightweight (0.25 kg) finger exoskeleton (TIE-EXO) for quantifying interactive impedance and finger fatigue. A resist-as-needed (RAN) controller was used to produce variable resistance in fingers’ exercises. The TIE-EXO’s feedback and RAN’s... |
Computing the positioning error of an upper-arm robotic prosthesis from the observation of its wearer’s posture | https://ieeexplore.ieee.org/document/9561613/ | [
"Alexis Poignant",
"Mathilde Legrand",
"Nathanaël Jarrassé",
"Guillaume Morel",
"Alexis Poignant",
"Mathilde Legrand",
"Nathanaël Jarrassé",
"Guillaume Morel"
] | When the arm prosthesis worn by an amputated Human being is not adequately configured with respect to the end-effector task, body compensations are often observed. Namely, to compensate for a wrong joint positioning on the robotic distal side, a subject trying to reach a desired position/orientation of his/her hand mobilizes his/her proximal joints, thus exploiting the redundancy of the human+robo... |
Intent-aware control in kinematically redundant systems: Towards collaborative wearable robots | https://ieeexplore.ieee.org/document/9561351/ | [
"Mahdi Khoramshahi",
"Guillaume Morel",
"Nathanael Jarrassé",
"Mahdi Khoramshahi",
"Guillaume Morel",
"Nathanael Jarrassé"
] | Many human-robot collaboration scenarios can be seen as a redundant leader-follower setup where the human (i.e., the leader) can potentially perform the task without the assistance of the robot (i.e., the follower). Thus, the goal of the collaboration, beside stable execution of the task, is to reduce the human cost; e.g., ergonomic, or cognitive cost. Such system redundancies (where the same task... |
Design, Development and Validation of a Dynamic Fall Prediction System for Excavators | https://ieeexplore.ieee.org/document/9560796/ | [
"Alfredo Argiolas",
"Simona Casini",
"Kazuhiro Fujio",
"Toshifumi Hiramatsu",
"Satoshi Morita",
"Matteo Ragaglia",
"Hisashi Sugiura",
"Marta Niccolini",
"Alfredo Argiolas",
"Simona Casini",
"Kazuhiro Fujio",
"Toshifumi Hiramatsu",
"Satoshi Morita",
"Matteo Ragaglia",
"Hisashi Sugiura",
"Marta Niccolini"
] | Safety can be listed as one of the most important aspects of every working environment, from the low risky to the most dangerous one. Construction sites can be clearly identified among the riskiest working fields, mainly because several complex and fast maneuvers are executed in a very crowded, dynamic and uncertain scenario. Specifically referring to construction machines, typical operations such... |
Feasible and Adaptive Multimodal Trajectory Prediction with Semantic Maneuver Fusion | https://ieeexplore.ieee.org/document/9561380/ | [
"Hendrik Berkemeyer",
"Riccardo Franceschini",
"Tuan Tran",
"Lin Che",
"Gordon Pipa",
"Hendrik Berkemeyer",
"Riccardo Franceschini",
"Tuan Tran",
"Lin Che",
"Gordon Pipa"
] | Predicting trajectories of participating vehicles is a crucial task towards full and safe autonomous driving. General unconstrained machine learning methods often report unrealistic predictions, and need to be combined with different motion constraints. Existing work either defines some shallow maneuvers and modes to regulate the output, or uses vehicle dynamics as the main source of constraints, ... |
Exploiting latent representation of sparse semantic layers for improved short-term motion prediction with Capsule Networks | https://ieeexplore.ieee.org/document/9561467/ | [
"Albert Dulian",
"John C. Murray",
"Albert Dulian",
"John C. Murray"
] | As urban environments manifest high levels of complexity it is of vital importance that safety systems embedded within autonomous vehicles (AVs) are able to accurately anticipate short-term future motion of nearby agents. This problem can be further understood as generating a sequence of coordinates describing the future motion of the tracked agent. Various proposed approaches demonstrate signific... |
Movement recognition and prediction using DMPs | https://ieeexplore.ieee.org/document/9562001/ | [
"Ali H. Kordia",
"Francisco S. Melo",
"Ali H. Kordia",
"Francisco S. Melo"
] | This paper proposes an approach for (a) recognizing an observed trajectory from a library of pre-learned motions; and (b) predicting the target position of such trajectory. In our approach, motions are represented as Dynamic Movement Primitives (DMPs). We use critical points from the observed trajectory to time-align it with those in the library. To match the observed trajectory with those in the ... |
Whole Body Model Predictive Control with a Memory of Motion: Experiments on a Torque-Controlled Talos | https://ieeexplore.ieee.org/document/9560742/ | [
"Ewen Dantec",
"Rohan Budhiraja",
"Adria Roig",
"Teguh Lembono",
"Guilhem Saurel",
"Olivier Stasse",
"Pierre Fernbach",
"Steve Tonneau",
"Sethu Vijayakumar",
"Sylvain Calinon",
"Michel Taix",
"Nicolas Mansard",
"Ewen Dantec",
"Rohan Budhiraja",
"Adria Roig",
"Teguh Lembono",
"Guilhem Saurel",
"Olivier Stasse",
"Pierre Fernbach",
"Steve Tonneau",
"Sethu Vijayakumar",
"Sylvain Calinon",
"Michel Taix",
"Nicolas Mansard"
] | This paper presents the first successful experiment implementing whole-body model predictive control with state feedback on a torque-control humanoid robot. We demonstrate that our control scheme is able to do whole-body target tracking, control the balance in front of strong external perturbations and avoid collision with an external object. The key elements for this success are threefold. First,... |
Constraint Handling in Continuous-Time DDP-Based Model Predictive Control | https://ieeexplore.ieee.org/document/9560795/ | [
"Jean-Pierre Sleiman",
"Farbod Farshidian",
"Marco Hutter",
"Jean-Pierre Sleiman",
"Farbod Farshidian",
"Marco Hutter"
] | The Sequential Linear Quadratic (SLQ) algorithm is a continuous-time version of the well-known Differential Dynamic Programming (DDP) technique with a Gauss-Newton Hessian approximation. This family of methods has gained popularity in the robotics community due to its efficiency in solving complex trajectory optimization problems. However, one major drawback of DDP-based formulations is their inab... |
Sparsity-Inducing Optimal Control via Differential Dynamic Programming | https://ieeexplore.ieee.org/document/9560961/ | [
"Traiko Dinev",
"Wolfgang Merkt",
"Vladimir Ivan",
"Ioannis Havoutis",
"Sethu Vijayakumar",
"Traiko Dinev",
"Wolfgang Merkt",
"Vladimir Ivan",
"Ioannis Havoutis",
"Sethu Vijayakumar"
] | Optimal control is a popular approach to synthesize highly dynamic motion. Commonly, L2 regularization is used on the control inputs in order to minimize energy used and to ensure smoothness of the control inputs. However, for some systems, such as satellites, the control needs to be applied in sparse bursts due to how the propulsion system operates. In this paper, we study approaches to induce sp... |
A Passive Navigation Planning Algorithm for Collision-free Control of Mobile Robots | https://ieeexplore.ieee.org/document/9561377/ | [
"Carlo Tiseo",
"Vladimir Ivan",
"Wolfgang Merkt",
"Ioannis Havoutis",
"Michael Mistry",
"Sethu Vijayakumar",
"Carlo Tiseo",
"Vladimir Ivan",
"Wolfgang Merkt",
"Ioannis Havoutis",
"Michael Mistry",
"Sethu Vijayakumar"
] | Path planning and collision avoidance are challenging in complex and highly variable environments due to the limited horizon of events. In literature, there are multiple model- and learning-based approaches that require significant computational resources to be effectively deployed and they may have limited generality. We propose a planning algorithm based on a globally stable passive controller t... |
Expansive Voronoi Tree: A Motion Planner for Assembly Sequence Planning | https://ieeexplore.ieee.org/document/9561346/ | [
"Sebastian Dorn",
"Nicola Wolpert",
"Elmar Schömer",
"Sebastian Dorn",
"Nicola Wolpert",
"Elmar Schömer"
] | One major challenge in Assembly Sequence Planning (ASP) for complex real-world CAD-scenarios is to find an appropriate disassembly path for each assembled part. Complex real-world scenes are characterized by a large installation space. There each part has many different possible disassembly paths that differ in length and clearance. However, due to tight packing in the installation space, these pa... |
MS2MP: A Min-Sum Message Passing Algorithm for Motion Planning | https://ieeexplore.ieee.org/document/9561533/ | [
"Salman Bari",
"Volker Gabler",
"Dirk Wollherr",
"Salman Bari",
"Volker Gabler",
"Dirk Wollherr"
] | Gaussian Process (GP) formulation of continuous-time trajectory offers a fast solution to the motion planning problem via probabilistic inference on factor graph. However, often the solution converges to in-feasible local minima and the planned trajectory is not collision-free. We propose a message passing algorithm that is more sensitive to obstacles with fast convergence time. We leverage the ut... |
Cubic Bézier Local Path Planner for Non-holonomic Feasible and Comfortable Path Generation | https://ieeexplore.ieee.org/document/9560854/ | [
"Guillaume Vailland",
"Valérie Gouranton",
"Marie Babel",
"Guillaume Vailland",
"Valérie Gouranton",
"Marie Babel"
] | In the case of non-holonomic robot navigation, path planning algorithms such as Rapidly-exploring Random Tree (RRT) rarely provide feasible and smooth paths without the need of additional processing. Furthermore, in a transport context like power wheelchair navigation, passenger comfort should be a priority and influence path planning strategy. In this paper, we propose a local path planner which ... |
Voxplan: A 3D Global Planner using Signed Distance Function Submaps | https://ieeexplore.ieee.org/document/9560819/ | [
"Laura Gasser",
"Alexander Millane",
"Victor Reijgwart",
"Rik Bähnemann",
"Roland Siegwart",
"Laura Gasser",
"Alexander Millane",
"Victor Reijgwart",
"Rik Bähnemann",
"Roland Siegwart"
] | The ability to safely navigate through complex and cluttered environments is required for a wide range of robotics applications. This paper introduces a framework to compute safe global paths in maps represented as collections of 3D Signed Distance Function (SDF) submaps. Such maps are able to maintain global consistency in spite of odometry drift. However, computationally efficient global path pl... |
Globally Optimal Online Redundancy Resolution for Serial 7-DOF Kinematics Along SE(3) Trajectories | https://ieeexplore.ieee.org/document/9560810/ | [
"Gerold Huber",
"Dirk Wollherr",
"Gerold Huber",
"Dirk Wollherr"
] | Redundant robots offer the possibility of improving agility, compared to their non-redundant counterparts, by exploiting the additional kinematic DOFs to increase a measure called manipulability. While it is common to maximize the manipulability measure during redundancy resolution locally, global optimization of a full trajectory is usually computationally too expensive and thus only considered f... |
Robot Arm Motion Planning Based on Geodesics | https://ieeexplore.ieee.org/document/9561180/ | [
"Mario Laux",
"Andreas Zell",
"Mario Laux",
"Andreas Zell"
] | Naturally, finding joint trajectories for robotic manipulators involves competing optimization goals. On the one hand, the end-effector should move along a predictable and short path while on the other hand joint movement and acceleration should be kept to a minimum. Obstacles in the workspace or joint limits complicate the situation even further. Constructing a metric that makes undesired configu... |
FlexDMP – Extending Dynamic Movement Primitives towards Flexible Joint Robots | https://ieeexplore.ieee.org/document/9560843/ | [
"Arne Wahrburg",
"Simone Guida",
"Nima Enayati",
"Andrea Maria Zanchettin",
"Paolo Rocco",
"Arne Wahrburg",
"Simone Guida",
"Nima Enayati",
"Andrea Maria Zanchettin",
"Paolo Rocco"
] | Dynamic Movement Primitives (DMPs) are a well-known tool for encoding robotic motions. Their popularity stems from invariance properties in time and space, the ability to describe complex coordinated motions in multiple degrees of freedom with a relatively small number of parameters, and the linearity in the parameters that describe the motion. The latter allows easily fitting a DMP to motions e.g... |
ManhattanSLAM: Robust Planar Tracking and Mapping Leveraging Mixture of Manhattan Frames | https://ieeexplore.ieee.org/document/9562030/ | [
"Raza Yunus",
"Yanyan Li",
"Federico Tombari",
"Raza Yunus",
"Yanyan Li",
"Federico Tombari"
] | In this paper, a robust RGB-D SLAM system is proposed to utilize the structural information in indoor scenes, allowing for accurate tracking and efficient dense mapping on a CPU. Prior works have used the Manhattan World (MW) assumption to estimate low-drift camera pose, in turn limiting the applications of such systems. This paper, in contrast, proposes a novel approach delivering robust tracking... |
Weighted Node Mapping and Localisation on a Pixel Processor Array | https://ieeexplore.ieee.org/document/9561524/ | [
"Hector Castillo-Elizalde",
"Yanan Liu",
"Laurie Bose",
"Walterio Mayol-Cuevas",
"Hector Castillo-Elizalde",
"Yanan Liu",
"Laurie Bose",
"Walterio Mayol-Cuevas"
] | This paper implements and demonstrates visual route mapping and localisation upon a Pixel Processor Array (PPA). The PPA sensor comprises of an array of Processing Elements (PEs), each of which can capture and process visual information directly. This provides significant parallel processing power allowing novel ways in which information can be processed on-sensor. Our method predicts the correct ... |
SoftMP: Attentive feature pooling for joint local feature detection and description for place recognition in changing environments | https://ieeexplore.ieee.org/document/9562087/ | [
"Fangming Yuan",
"Peer Neubert",
"Stefan Schubert",
"Peter Protzel",
"Fangming Yuan",
"Peer Neubert",
"Stefan Schubert",
"Peter Protzel"
] | Visual place recognition is the task of finding matchings of images that show the same place in the world. Combinations of appearance changes (e.g. changing illumination or weather) and geometric changes (e.g. viewpoint changes or occlusions) challenge existing approaches. Learning-based local image feature pipelines are a promising approach to this type of problem. We present a novel attentive fe... |
Beyond ANN: Exploiting Structural Knowledge for Efficient Place Recognition | https://ieeexplore.ieee.org/document/9561006/ | [
"Stefan Schubert",
"Peer Neubert",
"Peter Protzel",
"Stefan Schubert",
"Peer Neubert",
"Peter Protzel"
] | Visual place recognition is the task of recognizing same places of query images in a set of database images. It is important for loop closure detection in SLAM and candidate selection for global localization. Many approaches in the literature perform computationally inefficient full image comparisons between queries and all database images. There is still a lack of suited methods for efficient pla... |
Simultaneous Multi-Level Descriptor Learning and Semantic Segmentation for Domain-Specific Relocalization | https://ieeexplore.ieee.org/document/9561964/ | [
"Xiaolong Wu",
"Yiye Chen",
"Cédric Pradalier",
"Patricio A. Vela",
"Xiaolong Wu",
"Yiye Chen",
"Cédric Pradalier",
"Patricio A. Vela"
] | This paper presents a semi-supervised framework for multi-level description learning aiming for robust and accurate camera relocalization across large perception variations. Our proposed network, namely DLSSNet, simultaneously learns weakly-supervised semantic segmentation and local feature description in the hierarchy. Therefore, the augmented descriptors, trained in an end-to-end manner, provide... |
RADIATE: A Radar Dataset for Automotive Perception in Bad Weather | https://ieeexplore.ieee.org/document/9562089/ | [
"Marcel Sheeny",
"Emanuele De Pellegrin",
"Saptarshi Mukherjee",
"Alireza Ahrabian",
"Sen Wang",
"Andrew Wallace",
"Marcel Sheeny",
"Emanuele De Pellegrin",
"Saptarshi Mukherjee",
"Alireza Ahrabian",
"Sen Wang",
"Andrew Wallace"
] | Datasets for autonomous cars are essential for the development and benchmarking of perception systems. However, most existing datasets are captured with camera and LiDAR sensors in good weather conditions. In this paper, we present the RAdar Dataset In Adverse weaThEr (RADIATE), aiming to facilitate research on object detection, tracking and scene understanding using radar sensing for safe autonom... |
Poisson Surface Reconstruction for LiDAR Odometry and Mapping | https://ieeexplore.ieee.org/document/9562069/ | [
"Ignacio Vizzo",
"Xieyuanli Chen",
"Nived Chebrolu",
"Jens Behley",
"Cyrill Stachniss",
"Ignacio Vizzo",
"Xieyuanli Chen",
"Nived Chebrolu",
"Jens Behley",
"Cyrill Stachniss"
] | Accurately localizing in and mapping an environment are essential building blocks of most autonomous systems. In this paper, we present a novel approach for LiDAR odometry and mapping, focusing on improving the mapping quality and at the same time estimating the pose of the vehicle. Our approach performs frame-to-mesh ICP, but in contrast to other SLAM approaches, we represent the map as a triangl... |
Lidar-Monocular Surface Reconstruction Using Line Segments | https://ieeexplore.ieee.org/document/9561437/ | [
"Victor Amblard",
"Timothy P. Osedach",
"Arnaud Croux",
"Andrew Speck",
"John J. Leonard",
"Victor Amblard",
"Timothy P. Osedach",
"Arnaud Croux",
"Andrew Speck",
"John J. Leonard"
] | Structure from Motion (SfM) often fails to estimate accurate poses in environments that lack suitable visual features. In such cases, the quality of the final 3D mesh, which is contingent on the accuracy of those estimates, is reduced. One way to overcome this problem is to combine data from a monocular camera with that of a LIDAR. This allows fine details and texture to be captured while still ac... |
Balancing on a Springy Leg | https://ieeexplore.ieee.org/document/9561615/ | [
"Juan D. Gamba",
"Roy Featherstone",
"Juan D. Gamba",
"Roy Featherstone"
] | This paper presents a simulation study of the problem of balancing a planar double pendulum in which the lower body (the leg) has been modified to include a spring-loaded passive prismatic joint. Robots of this kind can travel by hopping, and can also stand and balance on a single point. The purpose of this study is to investigate the degree to which a balance controller can cope with the large an... |
Gyrubot: nonanthropomorphic stabilization for a biped | https://ieeexplore.ieee.org/document/9561214/ | [
"Nikita Mikhalkov",
"Alexey Prutskiy",
"Semyon Sechenev",
"Dmitry Kazakov",
"Alexey Simulin",
"Dmitry Sokolov",
"Igor Ryadchikov",
"Nikita Mikhalkov",
"Alexey Prutskiy",
"Semyon Sechenev",
"Dmitry Kazakov",
"Alexey Simulin",
"Dmitry Sokolov",
"Igor Ryadchikov"
] | Demands on leg degrees of freedom and control precision for bipedal robotics are steadily increasing, especially for the tasks involving walking on a rough terrain. In this paper we present an alternative, as well as a working proof-of-concept. Meet gyrubot: a 5-link almost planar bipedal robot with a torso complemented by a nonanthropomorphic stabilization system, capable of blindly walking throu... |
A novel method for computing the 3D friction cone using complimentary constraints | https://ieeexplore.ieee.org/document/9561800/ | [
"Dean Pretorius",
"Callen Fisher",
"Dean Pretorius",
"Callen Fisher"
] | Modeling the Coulomb Friction Cone in trajectory optimization is typically done by linearizing it along a series of vectors. Often, these vectors define the edges of polyhedral estimations of the cone. This article provides an alternate approach that samples the cone along a vector that satisfies the Maximum Dissipation Principle, which is shown to be significantly more computationally tractable. ... |
Learning Behavior Trees with Genetic Programming in Unpredictable Environments | https://ieeexplore.ieee.org/document/9562088/ | [
"Matteo Iovino",
"Jonathan Styrud",
"Pietro Falco",
"Christian Smith",
"Matteo Iovino",
"Jonathan Styrud",
"Pietro Falco",
"Christian Smith"
] | Modern industrial applications require robots to operate in unpredictable environments, and programs to be created with a minimal effort, to accommodate frequent changes to the task. Here, we show that genetic programming can be effectively used to learn the structure of a behavior tree (BT) to solve a robotic task in an unpredictable environment. We propose to use a simple simulator for learning,... |
Learning Efficient Constraint Graph Sampling for Robotic Sequential Manipulation | https://ieeexplore.ieee.org/document/9560978/ | [
"Joaquim Ortiz-Haro",
"Valentin N. Hartmann",
"Ozgur S. Oguz",
"Marc Toussaint",
"Joaquim Ortiz-Haro",
"Valentin N. Hartmann",
"Ozgur S. Oguz",
"Marc Toussaint"
] | Efficient sampling from constraint manifolds, and thereby generating a diverse set of solutions for feasibility problems, is a fundamental challenge. We consider the case where a problem is factored, that is, the underlying nonlinear program is decomposed into differentiable equality and inequality constraints, each of which depends only on some variables. Such problems are at the core of efficien... |
Coarse-to-Fine Imitation Learning: Robot Manipulation from a Single Demonstration | https://ieeexplore.ieee.org/document/9560942/ | [
"Edward Johns",
"Edward Johns"
] | We introduce a simple new method for visual imitation learning, which allows a novel robot manipulation task to be learned from a single human demonstration, without requiring any prior knowledge of the object being interacted with. Our method models imitation learning as a state estimation problem, with the state defined as the end-effector’s pose at the point where object interaction begins, as ... |
Predicting Disparity Distributions | https://ieeexplore.ieee.org/document/9561617/ | [
"Gustav Häger",
"Mikael Persson",
"Michael Felsberg",
"Gustav Häger",
"Mikael Persson",
"Michael Felsberg"
] | We investigate a novel deep-learning-based approach to estimate uncertainty in stereo disparity prediction networks. Current state-of-the-art methods often formulate disparity prediction as a regression problem with a single scalar output in each pixel. This can be problematic in practical applications as in many cases there might not exist a single well defined disparity, for example in cases of ... |
Scoring Graspability based on Grasp Regression for Better Grasp Prediction | https://ieeexplore.ieee.org/document/9561198/ | [
"Amaury Depierre",
"Emmanuel Dellandréa",
"Liming Chen",
"Amaury Depierre",
"Emmanuel Dellandréa",
"Liming Chen"
] | Grasping objects is one of the most important abilities that a robot needs to master in order to interact with its environment. Current state-of-the-art methods rely on deep neural networks trained to jointly predict a graspability score together with a regression of an offset with respect to grasp reference parameters. However, these two predictions are performed independently, which can lead to ... |
MonoSOD: Monocular Salient Object Detection based on Predicted Depth | https://ieeexplore.ieee.org/document/9561211/ | [
"George Dimas",
"Panagiota Gatoula",
"Dimitris K. Iakovidis",
"George Dimas",
"Panagiota Gatoula",
"Dimitris K. Iakovidis"
] | Salient object detection (SOD) can directly improve the performance of tasks like obstacle detection, semantic segmentation and object recognition. Such tasks are important for robotic and other autonomous navigation systems. State-of-the-art SOD methodologies, provide improved performance by incorporating depth information, usually acquired using additional specialized sensors, e.g., RGB-D camera... |
Fast Footstep Planning with Aborting A | https://ieeexplore.ieee.org/document/9561493/ | [
"Marcell Missura",
"Maren Bennewitz",
"Marcell Missura",
"Maren Bennewitz"
] | Footstep planning is the dominating approach when it comes to controlling the walk of a humanoid robot, even though a footstep plan is expensive to compute. The most prominent proposals typically spend up to a few seconds of computation time and output a sequence of up to 30 steps all the way to the goal. This way, footstep planning is applicable only in static environments where nothing changes a... |
Exploiting visual servoing and centroidal momentum for whole-body motion control of humanoid robots in absence of contacts and gravity | https://ieeexplore.ieee.org/document/9560739/ | [
"Enrico Mingo Hoffman",
"Antonio Paolillo",
"Enrico Mingo Hoffman",
"Antonio Paolillo"
] | The big potential of humanoid robots is not restricted to the ground, but these versatile machines can be successfully employed in unconventional scenarios, e.g. space, where contacts are not always present. In these situations, the robot’s limbs can be used to assist or even generate the angular motion of the floating base, as a consequence of the centroidal momentum conservation. In this paper, ... |
Virtual Adversarial Humans finding Hazards in Robot Workplaces | https://ieeexplore.ieee.org/document/9561668/ | [
"Tom P. Huck",
"Christoph Ledermann",
"Torsten Kröger",
"Tom P. Huck",
"Christoph Ledermann",
"Torsten Kröger"
] | During the planning phase of industrial robot workplaces, hazard analyses are required so that potential hazards for human workers can be identified and appropriate safety measures can be implemented. Existing hazard analysis methods use human reasoning, checklists and/or abstract system models, which limit the level of detail. We propose a new approach that frames hazard analysis as a search prob... |
Crowd against the machine: A simulation-based benchmark tool to evaluate and compare robot capabilities to navigate a human crowd | https://ieeexplore.ieee.org/document/9561694/ | [
"Fabien Grzeskowiak",
"David Gonon",
"Daniel Dugas",
"Diego Paez-Granados",
"Jen Jen Chung",
"Juan Nieto",
"Roland Siegwart",
"Aude Billard",
"Marie Babel",
"Julien Pettré",
"Fabien Grzeskowiak",
"David Gonon",
"Daniel Dugas",
"Diego Paez-Granados",
"Jen Jen Chung",
"Juan Nieto",
"Roland Siegwart",
"Aude Billard",
"Marie Babel",
"Julien Pettré"
] | The evaluation of robot capabilities to navigate human crowds is essential to conceive new robots intended to operate in public spaces. This paper initiates the development of a benchmark tool to evaluate such capabilities; our long term vision is to provide the community with a simulation tool that generates virtual crowded environment to test robots, to establish standard scenarios and metrics t... |
A Unified Perception Benchmark for Capacitive Proximity Sensing Towards Safe Human-Robot Collaboration (HRC) | https://ieeexplore.ieee.org/document/9561224/ | [
"Serkan Ergun",
"Yitao Ding",
"Hosam Alagi",
"Christian Schöffmann",
"Barnaba Ubezio",
"Gergely Soti",
"Michael Rathmair",
"Stephan Mühlbacher-Karrer",
"Ulrike Thomas",
"Björn Hein",
"Michael Hofbaur",
"Hubert Zangl",
"Serkan Ergun",
"Yitao Ding",
"Hosam Alagi",
"Christian Schöffmann",
"Barnaba Ubezio",
"Gergely Soti",
"Michael Rathmair",
"Stephan Mühlbacher-Karrer",
"Ulrike Thomas",
"Björn Hein",
"Michael Hofbaur",
"Hubert Zangl"
] | During the co-presence of human workers and robots, measures are required to avoid injuries from undesired contacts. Capacitive Proximity Sensors (CPSs) offer a cost-effective solution to cover the entire robot manipulator with fast close-range perception for HRC tasks, closing the perception gap between tactile detection and mid-range perception. CPSs do not suffer from occlusion and compared to ... |
Learning Human-like Hand Reaching for Human-Robot Handshaking | https://ieeexplore.ieee.org/document/9560746/ | [
"Vignesh Prasad",
"Ruth Stock-Homburg",
"Jan Peters",
"Vignesh Prasad",
"Ruth Stock-Homburg",
"Jan Peters"
] | One of the first and foremost non-verbal interactions that humans perform is a handshake. It has an impact on first impressions as touch can convey complex emotions. This makes handshaking an important skill for the repertoire of a social robot. In this paper, we present a novel framework for learning reaching behaviours for humanrobot handshaking behaviours for humanoid robots solely using third-... |
Simultaneous haptic guidance and learning of task parameters during robotic teleoperation – a geometrical approach | https://ieeexplore.ieee.org/document/9560938/ | [
"Thibault Poignonec",
"Florent Nageotte",
"Nabil Zemiti",
"Bernard Bayle",
"Thibault Poignonec",
"Florent Nageotte",
"Nabil Zemiti",
"Bernard Bayle"
] | Haptic guidance can improve accuracy and dexterity during the teleoperation of a robot, but only if the model of the task used to provide the assistance is accurate. In medical robotics, the registration of a task from pre-operative planning from medical images to the robot’s task-space can be erroneous. Additionally, the deformability of the environment can require online correction of a planned ... |
Human-Like Artificial Skin Sensor for Physical Human-Robot Interaction | https://ieeexplore.ieee.org/document/9561152/ | [
"Marc Teyssier",
"Brice Parilusyan",
"Anne Roudaut",
"Jürgen Steimle",
"Marc Teyssier",
"Brice Parilusyan",
"Anne Roudaut",
"Jürgen Steimle"
] | Physical Human-Robot-Interaction (pHRI) is beneficial for communication in social interaction or to perform collaborative tasks but is also crucial for safety. While robotic devices embed sensors for this sole purpose, their design often is the results of a trade-off between technical capabilities and rarely considers human factors. We propose a novel approach to design and fabricate compliant Hum... |
A Reversible Dynamic Movement Primitive formulation | https://ieeexplore.ieee.org/document/9562059/ | [
"Antonis Sidiropoulos",
"Zoe Doulgeri",
"Antonis Sidiropoulos",
"Zoe Doulgeri"
] | In this work, a novel Dynamic Movement Primitive (DMP) formulation is proposed which supports reversibility, i.e. backwards reproduction of a learned trajectory. Apart from sharing all favourable properties of the original DMP, decoupling the teaching of position and velocity profiles and bidirectional drivability along the encoded path are also supported. Original DMP have been extensively used f... |
Towards efficient human-robot cooperation for socially-aware robot navigation in human-populated environments: the SNAPE framework | https://ieeexplore.ieee.org/document/9561448/ | [
"A. Vega-Magro",
"R. Gondkar",
"L.J. Manso",
"P. Núñez",
"A. Vega-Magro",
"R. Gondkar",
"L.J. Manso",
"P. Núñez"
] | It is widely accepted that in the future, robots will cooperate with humans in everyday tasks. Robots interacting with humans will require social awareness when performing their tasks which will require navigation. While navigating, robots should aim to avoid distressing people in order to maximize their chance of social acceptance. For instance, avoiding getting too close to people or disrupting ... |
Analysis of Open-Loop Grasping From Piles | https://ieeexplore.ieee.org/document/9561065/ | [
"Előd Páll",
"Oliver Brock",
"Előd Páll",
"Oliver Brock"
] | This paper offers an explanation of why humans can effortlessly grasp objects from a pile. We identified a regularity in objects’ motion when pushed, namely, an object separates and stabilizes in front of the pusher. We devise an open-loop grasping strategy leveraging this regularity in piles of nearly identical objects. Our real robot robustly grasps round objects beside a wall with success rates... |
Human Initiated Grasp Space Exploration Algorithm for an Underactuated Robot Gripper Using Variational Autoencoder | https://ieeexplore.ieee.org/document/9561765/ | [
"Clément Rolinat",
"Mathieu Grossard",
"Saifeddine Aloui",
"Christelle Godin",
"Clément Rolinat",
"Mathieu Grossard",
"Saifeddine Aloui",
"Christelle Godin"
] | Grasp planning and most specifically the grasp space exploration is still an open issue in robotics. This article presents an efficient procedure for exploring the grasp space of a multifingered adaptive gripper for generating reliable grasps given a known object pose. This procedure relies on a limited dataset of manually specified expert grasps, and use a mixed analytic and data-driven approach ... |
An Underactuated Gripper based on Car Differentials for Self-Adaptive Grasping with Passive Disturbance Rejection | https://ieeexplore.ieee.org/document/9561725/ | [
"Qiujie Lu",
"Jinhong Wang",
"Zhuang Zhang",
"Genliang Chen",
"Hao Wang",
"Nicolas Rojas",
"Qiujie Lu",
"Jinhong Wang",
"Zhuang Zhang",
"Genliang Chen",
"Hao Wang",
"Nicolas Rojas"
] | We introduce an underactuated differential-based robot gripper able to perform self-adaptive grasping with passive disturbance rejection. The gripper utilises three car differential systems to achieve self-adaptiveness with a single actuator: a base differential for distributing power from the motor to the fingers, and two independent finger differentials for controlling the proximal and distal jo... |
Data-driven sea state estimation for vessels using multi-domain features from motion responses | https://ieeexplore.ieee.org/document/9561261/ | [
"Peihua Han",
"Guoyuan Li",
"Stian Skjong",
"Baiheng Wu",
"Houxiang Zhang",
"Peihua Han",
"Guoyuan Li",
"Stian Skjong",
"Baiheng Wu",
"Houxiang Zhang"
] | Situation awareness is of great importance for autonomous ships. One key aspect is to estimate the sea state in a real-time manner. Considering the ship as a large wave buoy, the sea state can be estimated from motion responses without extra sensors installed. However, it is difficult to associate waves with ship motion through an explicit model since the hydrodynamic effect is hard to model. In t... |
A Fault Tolerant Control Architecture Based on Fault Trees for an Underwater Robot Executing Transect Missions | https://ieeexplore.ieee.org/document/9561735/ | [
"Adrien Hereau",
"Karen Godary-Dejean",
"Jérémie Guiochet",
"Didier Crestani",
"Adrien Hereau",
"Karen Godary-Dejean",
"Jérémie Guiochet",
"Didier Crestani"
] | Robotic systems evolving in hazardous and harsh environment are prone to mission failure or system loss in presence of faults. This paper presents a fault tolerant methodology, implemented into a control architecture of an underwater robot that executes biological monitoring missions. High level constraint violations (mission, safety, energy, time and localization) and low level faults (software a... |
Robust Underwater Visual SLAM Fusing Acoustic Sensing | https://ieeexplore.ieee.org/document/9561537/ | [
"Elizabeth Vargas",
"Raluca Scona",
"Jonatan Scharff Willners",
"Tomasz Luczynski",
"Yu Cao",
"Sen Wang",
"Yvan R. Petillot",
"Elizabeth Vargas",
"Raluca Scona",
"Jonatan Scharff Willners",
"Tomasz Luczynski",
"Yu Cao",
"Sen Wang",
"Yvan R. Petillot"
] | In this paper, we propose an approach for robust visual Simultaneous Localisation and Mapping (SLAM) in underwater environments leveraging acoustic, inertial and altimeter/depth sensors. Underwater visual SLAM is challenging due to factors including poor visibility caused by suspended particles in water, a lack of light and insufficient texture in the scene. Because of this, many state-of-the-art ... |
Real-time Friction Estimation for Grip Force Control | https://ieeexplore.ieee.org/document/9561640/ | [
"Heba Khamis",
"Benjamin Xia",
"Stephen J. Redmond",
"Heba Khamis",
"Benjamin Xia",
"Stephen J. Redmond"
] | An important capability of humans when performing dexterous precision gripping tasks is our ability to feel both the weight and slipperiness of an object in real-time, and adjust our grip force accordingly. In this paper, we present for the first time a fully-instrumented version of our PapillArray tactile sensor concept, which can sense grip force, object weight, and incipient slip and friction, ... |
Uncertainty-aware deep learning for robot touch: Application to Bayesian tactile servo control | https://ieeexplore.ieee.org/document/9562077/ | [
"Manuel Floriano Vázquez",
"Nathan F. Lepora",
"Manuel Floriano Vázquez",
"Nathan F. Lepora"
] | This work investigates uncertainty-aware deep learning (DL) in tactile robotics based on a general framework introduced recently for robot vision. For a test scenario, we consider optical tactile sensing in combination with DL to estimate the edge pose as a feedback signal to servo around various 2D test objects. We demonstrate that uncertainty-aware DL can improve the pose estimation over determi... |
Towards integrated tactile sensorimotor control in anthropomorphic soft robotic hands | https://ieeexplore.ieee.org/document/9561350/ | [
"Nathan F. Lepora",
"Chris Ford",
"Andrew Stinchcombe",
"Alfred Brown",
"John Lloyd",
"Manuel G. Catalano",
"Matteo Bianchi",
"Benjamin Ward-Cherrier",
"Nathan F. Lepora",
"Chris Ford",
"Andrew Stinchcombe",
"Alfred Brown",
"John Lloyd",
"Manuel G. Catalano",
"Matteo Bianchi",
"Benjamin Ward-Cherrier"
] | In this work, we report on how a sense of touch can be used to control an underactuated anthropomorphic robot hand, based on an integration that respects the hand’s mechanical functionality. Our focus is on integrating the sensorimotor control of the Pisa/IIT SoftHand, an anthropomorphic soft robot hand designed around the principle of adaptive synergies, with the BRL tactile fingertip (TacTip), a... |
An efficient approach to closed-loop shape control of deformable objects using finite element models | https://ieeexplore.ieee.org/document/9560919/ | [
"A. Koessler",
"N. Roca Filella",
"B.C. Bouzgarrou",
"L. Lequièvre",
"J.-A. Corrales Ramon",
"A. Koessler",
"N. Roca Filella",
"B.C. Bouzgarrou",
"L. Lequièvre",
"J.-A. Corrales Ramon"
] | Robots are nowadays faced with the challenge of handling deformable objects in industrial operations. In particular, the problem of shape control, which aims at giving a specific deformation state to an object, has gained interest recently in the research community. Among the proposed solutions, approaches based on finite elements proved accurate and reliable but also complex and computationally-i... |
Learning Stable Normalizing-Flow Control for Robotic Manipulation | https://ieeexplore.ieee.org/document/9562071/ | [
"Shahbaz Abdul Khader",
"Hang Yin",
"Pietro Falco",
"Danica Kragic",
"Shahbaz Abdul Khader",
"Hang Yin",
"Pietro Falco",
"Danica Kragic"
] | Reinforcement Learning (RL) of robotic manipulation skills, despite its impressive successes, stands to benefit from incorporating domain knowledge from control theory. One of the most important properties that is of interest is control stability. Ideally, one would like to achieve stability guarantees while staying within the framework of state-of-the-art deep RL algorithms. Such a solution does ... |
Model Predictive Robot-Environment Interaction Control for Mobile Manipulation Tasks | https://ieeexplore.ieee.org/document/9562066/ | [
"Maria Vittoria Minniti",
"Ruben Grandia",
"Kevin Fäh",
"Farbod Farshidian",
"Marco Hutter",
"Maria Vittoria Minniti",
"Ruben Grandia",
"Kevin Fäh",
"Farbod Farshidian",
"Marco Hutter"
] | Modern, torque-controlled service robots can regulate contact forces when interacting with their environment. Model Predictive Control (MPC) is a powerful method to solve the underlying control problem, allowing to plan for whole-body motions while including different constraints imposed by the robot dynamics or its environment. However, an accurate model of the robot-environment is needed to achi... |
Surgical Gesture Recognition Based on Bidirectional Multi-Layer Independently RNN with Explainable Spatial Feature Extraction | https://ieeexplore.ieee.org/document/9561803/ | [
"Dandan Zhang",
"Ruoxi Wang",
"Benny Lo",
"Dandan Zhang",
"Ruoxi Wang",
"Benny Lo"
] | Minimally invasive surgery mainly consists of a series of sub-tasks, which can be decomposed into basic gestures or contexts. As a prerequisite of autonomic operation, surgical gesture recognition can assist motion planning and decision-making, and build up context-aware knowledge to improve the surgical robot control quality. In this work, we aim to develop an effective surgical gesture recogniti... |
What data do we need for training an AV motion planner? | https://ieeexplore.ieee.org/document/9561723/ | [
"Long Chen",
"Lukas Platinsky",
"Stefanie Speichert",
"Błażej Osiński",
"Oliver Scheel",
"Yawei Ye",
"Hugo Grimmett",
"Luca Del Pero",
"Peter Ondruska",
"Long Chen",
"Lukas Platinsky",
"Stefanie Speichert",
"Błażej Osiński",
"Oliver Scheel",
"Yawei Ye",
"Hugo Grimmett",
"Luca Del Pero",
"Peter Ondruska"
] | We investigate what grade of sensor data is required for training an imitation-learning-based AV planner on human expert demonstration. Machine-learned planners [1] are very hungry for training data, which is usually collected using vehicles equipped with the same sensors used for autonomous operation [1]. This is costly and non-scalable. If cheaper sensors could be used for collection instead, da... |
Learn to Path: Using neural networks to predict Dubins path characteristics for aerial vehicles in wind | https://ieeexplore.ieee.org/document/9560879/ | [
"Trevor Phillips",
"Maximilian Stölzle",
"Erick Turricelli",
"Florian Achermann",
"Nicholas Lawrance",
"Roland Siegwart",
"Jen Jen Chung",
"Trevor Phillips",
"Maximilian Stölzle",
"Erick Turricelli",
"Florian Achermann",
"Nicholas Lawrance",
"Roland Siegwart",
"Jen Jen Chung"
] | For asymptotically optimal sampling-based path planners such as RRT*, path quality improves as the number of samples added to the motion tree increases. However, each additional sample requires a nearest-neighbor search. Calculating state transition costs can be particularly difficult in cases with complex dynamics such as aerial vehicles in non-isotropic cost fields like wind. Computationally cos... |
Automated Generation of Robot Trajectories for Assembly Processes Requiring Only Sparse Manual Input | https://ieeexplore.ieee.org/document/9561465/ | [
"Steffen Madsen",
"Milad Jami",
"Henrik G. Petersen",
"Steffen Madsen",
"Milad Jami",
"Henrik G. Petersen"
] | In this paper, a new method for offline programming part assembly operations with tight fittings is presented. More specifically, an assembly process trajectory generator with self programming capabilities is developed where the user needs to provide only very sparse and intuitive input. The presented system is added to the existing skill based robot software package VEROSIM. In VEROSIM, the traje... |
Benchmarking Real-Time Capabilities of ROS 2 and OROCOS for Robotics Applications | https://ieeexplore.ieee.org/document/9561026/ | [
"Sinan Barut",
"Marco Boneberger",
"Pouya Mohammadi",
"Jochen J. Steil",
"Sinan Barut",
"Marco Boneberger",
"Pouya Mohammadi",
"Jochen J. Steil"
] | Numerous robotic and control applications have strict real-time requirements, which, when violated, result in reduced quality of service or, in case of safety critical applications, might even have catastrophic consequences. To ensure that certain real-time constraints are satisfied, roboticists have relied on real-time safe frameworks, environments and middleware. With the introduction of ROS 2, ... |
The KIT Gripper: A Multi-Functional Gripper for Disassembly Tasks | https://ieeexplore.ieee.org/document/9561336/ | [
"Cornelius Klas",
"Felix Hundhausen",
"Jianfeng Gao",
"Christian R. G. Dreher",
"Stefan Reither",
"You Zhou",
"Tamim Asfour",
"Cornelius Klas",
"Felix Hundhausen",
"Jianfeng Gao",
"Christian R. G. Dreher",
"Stefan Reither",
"You Zhou",
"Tamim Asfour"
] | We introduce a multi-functional robotic gripper equipped with a set of actions required for disassembly of electromechanical devices. The gripper consists of a robot arm with 5 degrees of freedom (DoF) for manipulation and a jaw gripper with a 1-DoF rotation joint and a 1-DoF closing joint. The system enables manipulation in 7 DoF and offers the ability to reposition objects in hand and to perform... |
In-Process Workpiece Geometry Estimation for Robotic Arc Welding based on Supervised Learning for Multi-Sensor Inputs | https://ieeexplore.ieee.org/document/9561500/ | [
"Alexander Schmidt",
"Christian Kotschote",
"Oliver Riedel",
"Alexander Schmidt",
"Christian Kotschote",
"Oliver Riedel"
] | Due to manufacturing tolerances, the geometry parameters of workpieces are not constant in industrial welding applications. Today, this problem is addressed by either accepting fluctuating part quality or by measuring the geometry and adjusting the configuration of the robot and process controller for each individual part. However, measuring the geometry requires additional manufacturing time or r... |
Context-Dependent Anomaly Detection for Low Altitude Traffic Surveillance | https://ieeexplore.ieee.org/document/9562043/ | [
"Ilker Bozcan",
"Erdal Kayacan",
"Ilker Bozcan",
"Erdal Kayacan"
] | The detection of contextual anomalies is a challenging task for surveillance since an observation can be considered anomalous or normal in a specific environmental context. An unmanned aerial vehicle (UAV) can utilize its aerial monitoring capability and employ multiple sensors to gather contextual information about the environment and perform contextual anomaly detection. In this work, we introdu... |
Autonomous Flying into Buildings in a Firefighting Scenario | https://ieeexplore.ieee.org/document/9560789/ | [
"Vaclav Pritzl",
"Petr Stepan",
"Martin Saska",
"Vaclav Pritzl",
"Petr Stepan",
"Martin Saska"
] | We propose an approach enabling an Unmanned Aerial Vehicle (UAV) to autonomously enter a target building through an open window. We use a fusion of depth camera and 2D Light Detection and Ranging (LiDAR) data for window detection and continuous estimation of its position, orientation, and size. The proposed algorithms are capable of running both with and without available a priori information. The... |
Polyhedral Friction Cone Estimator for Object Manipulation | https://ieeexplore.ieee.org/document/9560807/ | [
"Morteza Azad",
"Silvia Cruciani",
"Michael J. Mathew",
"Graham Deacon",
"Guillaume de Chambrier",
"Morteza Azad",
"Silvia Cruciani",
"Michael J. Mathew",
"Graham Deacon",
"Guillaume de Chambrier"
] | A polyhedral friction cone is a set of reaction wrenches that an object can experience whilst in contact with its environment. This polyhedron is a powerful tool to control an object’s motion and interaction with the environment. It can be derived analytically, upon knowledge of object and environment geometries, contact point locations and friction coefficients. We propose to estimate the polyhed... |
Interpretability in Contact-Rich Manipulation via Kinodynamic Images | https://ieeexplore.ieee.org/document/9560920/ | [
"Ioanna Mitsioni",
"Joonatan Mänttäri",
"Yiannis Karayiannidis",
"John Folkesson",
"Danica Kragic",
"Ioanna Mitsioni",
"Joonatan Mänttäri",
"Yiannis Karayiannidis",
"John Folkesson",
"Danica Kragic"
] | Deep Neural Networks (NNs) have been widely utilized in contact-rich manipulation tasks to model the complicated contact dynamics. However, NN-based models are often difficult to decipher which can lead to seemingly inexplicable behaviors and unidentifiable failure cases. In this work, we address the interpretability of NN-based models by introducing the kinodynamic images. We propose a methodolog... |
Model-Free Reinforcement Learning for Stochastic Games with Linear Temporal Logic Objectives | https://ieeexplore.ieee.org/document/9561989/ | [
"Alper Kamil Bozkurt",
"Yu Wang",
"Michael M. Zavlanos",
"Miroslav Pajic",
"Alper Kamil Bozkurt",
"Yu Wang",
"Michael M. Zavlanos",
"Miroslav Pajic"
] | We study synthesis of control strategies from linear temporal logic (LTL) objectives in unknown environments. We model this problem as a turn-based zero-sum stochastic game between the controller and the environment, where the transition probabilities and the model topology are fully unknown. The winning condition for the controller in this game is the satisfaction of the given LTL specification, ... |
Secure Planning Against Stealthy Attacks via Model-Free Reinforcement Learning | https://ieeexplore.ieee.org/document/9560940/ | [
"Alper Kamil Bozkurt",
"Yu Wang",
"Miroslav Pajic",
"Alper Kamil Bozkurt",
"Yu Wang",
"Miroslav Pajic"
] | We consider the problem of security-aware planning in an unknown stochastic environment, in the presence of attacks on control signals (i.e., actuators) of the robot. We model the attacker as an agent who has the full knowledge of the controller as well as the employed intrusion-detection system and who wants to prevent the controller from performing tasks while staying stealthy. We formulate the ... |
Hierarchies of Planning and Reinforcement Learning for Robot Navigation | https://ieeexplore.ieee.org/document/9561151/ | [
"Jan Wöhlke",
"Felix Schmitt",
"Herke van Hoof",
"Jan Wöhlke",
"Felix Schmitt",
"Herke van Hoof"
] | Solving robotic navigation tasks via reinforcement learning (RL) is challenging due to their sparse reward and long decision horizon nature. However, in many navigation tasks, high-level (HL) task representations, like a rough floor plan, are available. Previous work has demonstrated efficient learning by hierarchal approaches consisting of path planning in the HL representation and using sub-goal... |
A Laser-based Dual-arm System for Precise Control of Collaborative Robots | https://ieeexplore.ieee.org/document/9561173/ | [
"João Silvério",
"Guillaume Clivaz",
"Sylvain Calinon",
"João Silvério",
"Guillaume Clivaz",
"Sylvain Calinon"
] | Collaborative robots offer increased interaction capabilities at relatively low cost but in contrast to their industrial counterparts they inevitably lack precision. Moreover, in addition to the robots' own imperfect models, day-to-day operations entail various sources of errors that despite being small rapidly accumulate. This happens as tasks change and robots are re-programmed, often requiring ... |
Near-Optimal Multi-Robot Motion Planning with Finite Sampling | https://ieeexplore.ieee.org/document/9561009/ | [
"Dror Dayan",
"Kiril Solovey",
"Marco Pavone",
"Dan Halperin",
"Dror Dayan",
"Kiril Solovey",
"Marco Pavone",
"Dan Halperin"
] | An underlying structure in several sampling-based methods for continuous multi-robot motion planning (MRMP) is the tensor roadmap (PR), which emerges from combining multiple PRM graphs constructed for the individual robots via a tensor product. We study the conditions under which the TR encodes a near-optimal solution for MRMP—satisfying these conditions implies near optimality for a variety of po... |
Whole-Body Real-Time Motion Planning for Multicopters | https://ieeexplore.ieee.org/document/9561526/ | [
"Shaohui Yang",
"Botao He",
"Zhepei Wang",
"Chao Xu",
"Fei Gao",
"Shaohui Yang",
"Botao He",
"Zhepei Wang",
"Chao Xu",
"Fei Gao"
] | Multicopters are able to perform high maneuverability yet their potential have not been fully achieved. In this work, we propose a full-body, optimization-based motion planning framework that takes shape and attitude of aerial robot into consideration such that the aggressiveness of drone maneuvering improves significantly in cluttered environment. Our method takes in a series of intersecting poly... |
Collision-Free MPC for Legged Robots in Static and Dynamic Scenes | https://ieeexplore.ieee.org/document/9561326/ | [
"Magnus Gaertner",
"Marko Bjelonic",
"Farbod Farshidian",
"Marco Hutter",
"Magnus Gaertner",
"Marko Bjelonic",
"Farbod Farshidian",
"Marco Hutter"
] | We present a model predictive controller (MPC) that automatically discovers collision-free locomotion while simultaneously taking into account the system dynamics, friction constraints, and kinematic limitations. A relaxed barrier function is added to the optimization’s cost function, leading to collision avoidance behavior without increasing the problem’s computational complexity. Our holistic ap... |
Obstacle Avoidance with Kinetic Energy Buffer | https://ieeexplore.ieee.org/document/9561458/ | [
"V. Pitkänen",
"T. Pennanen",
"A. Tikanmäki",
"J. Röning",
"V. Pitkänen",
"T. Pennanen",
"A. Tikanmäki",
"J. Röning"
] | This paper presents Kinetic Energy Difference (KED) as a metric for collision proximity. The calculation of KED for differentially driven robots is explained, along with an example obstacle avoidance algorithm that utilizes it. This example algorithm is computationally efficient and simulations show that it is capable of guiding robots with slow dynamics through narrow corridors. |
Learning from Simulation, Racing in Reality | https://ieeexplore.ieee.org/document/9562079/ | [
"Eugenio Chisari",
"Alexander Liniger",
"Alisa Rupenyan",
"Luc Van Gool",
"John Lygeros",
"Eugenio Chisari",
"Alexander Liniger",
"Alisa Rupenyan",
"Luc Van Gool",
"John Lygeros"
] | We present a reinforcement learning-based solution to autonomously race on a miniature race car platform. We show that a policy that is trained purely in simulation using a relatively simple vehicle model, including model randomization, can be successfully transferred to the real robotic setup. We achieve this by using a novel policy output regularization approach and a lifted action space which e... |
Equality Constrained Differential Dynamic Programming | https://ieeexplore.ieee.org/document/9561339/ | [
"Sarah El Kazdadi",
"Justin Carpentier",
"Jean Ponce",
"Sarah El Kazdadi",
"Justin Carpentier",
"Jean Ponce"
] | Trajectory optimization is an important tool in task-based robot motion planning, due to its generality and convergence guarantees under some mild conditions. It is often used as a post-processing operation to smooth out trajectories that are generated by probabilistic methods or to directly control the robot motion. Unconstrained trajectory optimization problems have been well studied, and are co... |
Unsupervised Motion Estimation of Vehicles Using ICP | https://ieeexplore.ieee.org/document/9561753/ | [
"Tom Roussel",
"Tinne Tuytelaars",
"Luc Van Eycken",
"Tom Roussel",
"Tinne Tuytelaars",
"Luc Van Eycken"
] | Anticipating the motion of dynamic objects is critical for making intelligent decisions navigating through an environment while avoiding collisions. In this work, we propose a CNN model that estimates 3D motion of objects using sequences of monocular images. We show that we can train this model without using any manual annotations by using Iterative Closest Points (ICP) to align pointclouds of an ... |
CNN-based Ego-Motion Estimation for Fast MAV Maneuvers | https://ieeexplore.ieee.org/document/9561714/ | [
"Yingfu Xu",
"Guido C. H. E. de Croon",
"Yingfu Xu",
"Guido C. H. E. de Croon"
] | In the field of visual ego-motion estimation for Micro Air Vehicles (MAVs), fast maneuvers stay challenging mainly because of the big visual disparity and motion blur. In the pursuit of higher robustness, we study convolutional neural networks (CNNs) that predict the relative pose between subsequent images from a fast-moving monocular camera facing a planar scene. Aided by the Inertial Measurement... |
Mid-Air Range-Visual-Inertial Estimator Initialization for Micro Air Vehicles | https://ieeexplore.ieee.org/document/9560913/ | [
"Martin Scheiber",
"Jeff Delaune",
"Stephan Weiss",
"Roland Brockers",
"Martin Scheiber",
"Jeff Delaune",
"Stephan Weiss",
"Roland Brockers"
] | Monocular Visual-Inertial Odometry (VIO) has become ubiquitous for navigation of autonomous Micro Air Vehicles (MAVs). Yet, state-of-the-art VIO is still very failure-prone, which can have dramatic consequences. To prevent this, VIO must be able to re-initialize in mid-air, either during a free fall or on a constant velocity trajectory after attitude control has been re-established. However, for b... |
Pose Estimation for Vehicle-mounted Cameras via Horizontal and Vertical Planes | https://ieeexplore.ieee.org/document/9561890/ | [
"Istvan Gergo Gal",
"Daniel Barath",
"Levente Hajder",
"Istvan Gergo Gal",
"Daniel Barath",
"Levente Hajder"
] | We propose novel solvers for estimating the egomotion of a calibrated camera mounted to a moving vehicle from a single affine correspondence via recovering special homographies. For the first, second and third classes of solvers, the sought plane is expected to be perpendicular to one of the camera axes. For the fourth class, the plane is orthogonal to the ground with unknown normal, e.g., it is a... |
Dynamic Occupancy Grid Mapping with Recurrent Neural Networks | https://ieeexplore.ieee.org/document/9561375/ | [
"Marcel Schreiber",
"Vasileios Belagiannis",
"Claudius Gläser",
"Klaus Dietmayer",
"Marcel Schreiber",
"Vasileios Belagiannis",
"Claudius Gläser",
"Klaus Dietmayer"
] | Modeling and understanding the environment is an essential task for autonomous driving. In addition to the detection of objects, in complex traffic scenarios the motion of other road participants is of special interest. Therefore, we propose to use a recurrent neural network to predict a dynamic occupancy grid map, which divides the vehicle surrounding in cells, each containing the occupancy proba... |
Automatic Mapping of Tailored Landmark Representations for Automated Driving and Map Learning | https://ieeexplore.ieee.org/document/9561432/ | [
"Jan-Hendrik Pauls",
"Benjamin Schmidt",
"Christoph Stiller",
"Jan-Hendrik Pauls",
"Benjamin Schmidt",
"Christoph Stiller"
] | While the automatic creation of maps for localization is a widely tackled problem, the automatic inference of higher layers of HD maps is not. Additionally, approaches that learn from maps require richer and more precise landmarks than currently available.In this work, we fuse semantic detections from a monocular camera with depth and orientation estimation from lidar to automatically detect, trac... |
Lightweight Semantic Mesh Mapping for Autonomous Vehicles | https://ieeexplore.ieee.org/document/9560996/ | [
"Markus Herb",
"Tobias Weiherer",
"Nassir Navab",
"Federico Tombari",
"Markus Herb",
"Tobias Weiherer",
"Nassir Navab",
"Federico Tombari"
] | Lightweight and semantically meaningful environment maps are crucial for many applications in robotics and autonomous driving to facilitate higher-level tasks such as navigation and planning. In this paper we present a novel approach to incrementally build a meaningful and lightweight semantic map directly as a 3D mesh from a monocular or stereo sequence. Our system leverages existing feature-base... |
LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping | https://ieeexplore.ieee.org/document/9560768/ | [
"Ozan Çatal",
"Wouter Jansen",
"Tim Verbelen",
"Bart Dhoedt",
"Jan Steckel",
"Ozan Çatal",
"Wouter Jansen",
"Tim Verbelen",
"Bart Dhoedt",
"Jan Steckel"
] | Biologically inspired algorithms for simultaneous localization and mapping (SLAM) such as RatSLAM have been shown to yield effective and robust robot navigation in both indoor and outdoor environments. One drawback however is the sensitivity to perceptual aliasing due to the template matching of low-dimensional sensory templates. In this paper, we propose an unsupervised representation learning me... |
Robot in a China Shop: Using Reinforcement Learning for Location-Specific Navigation Behaviour | https://ieeexplore.ieee.org/document/9561545/ | [
"Bian Xihan",
"Oscar Mendez",
"Simon Hadfield",
"Bian Xihan",
"Oscar Mendez",
"Simon Hadfield"
] | Robots need to be able to work in multiple different environments. Even when performing similar tasks, different behaviour should be deployed to best fit the current environment. In this paper, We propose a new approach to navigation, where it is treated as a multi-task learning problem. This enables the robot to learn to behave differently in visual navigation tasks for different environments whi... |
Model Identification of a Small Fully-Actuated Aquatic Surface Vehicle Using a Long Short-Term Memory Neural Network | https://ieeexplore.ieee.org/document/9561454/ | [
"Marin Dimitrov",
"Keir Groves",
"David Howard",
"Barry Lennox",
"Marin Dimitrov",
"Keir Groves",
"David Howard",
"Barry Lennox"
] | A long short-term memory neural network is used to provide a system model that captures the temporal-dynamics of a holonomic, fully-actuated aquatic surface vehicle. As is true in many fields, new developments in robotics often are made in simulation first before being applied to real systems. To simulate an aquatic or aerial robot, a dynamic system model of the robot is required. The more represe... |
Real-Time Trajectory Adaptation for Quadrupedal Locomotion using Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9561639/ | [
"Siddhant Gangapurwala",
"Mathieu Geisert",
"Romeo Orsolino",
"Maurice Fallon",
"Ioannis Havoutis",
"Siddhant Gangapurwala",
"Mathieu Geisert",
"Romeo Orsolino",
"Maurice Fallon",
"Ioannis Havoutis"
] | We present a control architecture for real-time adaptation and tracking of trajectories generated using a terrain-aware trajectory optimization solver. This approach enables us to circumvent the computationally exhaustive task of online trajectory optimization, and further introduces a control solution robust to systems modeled with approximated dynamics. We train a policy using deep reinforcement... |
Robust Iterative Learning Control for Pneumatic Muscle with State Constraint and Model Uncertainty | https://ieeexplore.ieee.org/document/9560892/ | [
"Kun Qian",
"Zhenghong Li",
"Ahmed Asker",
"Zhiqiang Zhang",
"Shengquan Xie",
"Kun Qian",
"Zhenghong Li",
"Ahmed Asker",
"Zhiqiang Zhang",
"Shengquan Xie"
] | In this paper, we propose a novel iterative learning control (ILC) scheme for precise state tracking of pneumatic muscle (PM) actuators. Two critical issues are considered in our scheme: 1) state constraints on PM position and velocity; 2) uncertainties of the PM model. Based on the three-element form, a PM model is constructed that takes both parametric and nonparametric uncertainties into consid... |
NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation | https://ieeexplore.ieee.org/document/9560932/ | [
"Zhicheng Zhou",
"Cheng Zhao",
"Daniel Adolfsson",
"Songzhi Su",
"Yang Gao",
"Tom Duckett",
"Li Sun",
"Zhicheng Zhou",
"Cheng Zhao",
"Daniel Adolfsson",
"Songzhi Su",
"Yang Gao",
"Tom Duckett",
"Li Sun"
] | 3D point cloud-based place recognition is highly demanded by autonomous driving in GPS-challenged environments and serves as an essential component (i.e. loop-closure detection) in lidar-based SLAM systems. This paper proposes a novel approach, named NDT-Transformer, for real-time and large-scale place recognition using 3D point clouds. Specifically, a 3D Normal Distribution Transform (NDT) repres... |
Implementation of a Reactive Walking Controller for the New Open-Hardware Quadruped Solo-12 | https://ieeexplore.ieee.org/document/9561559/ | [
"Pierre-Alexandre Léziart",
"Thomas Flayols",
"Felix Grimminger",
"Nicolas Mansard",
"Philippe Souères",
"Pierre-Alexandre Léziart",
"Thomas Flayols",
"Felix Grimminger",
"Nicolas Mansard",
"Philippe Souères"
] | This paper aims at showing the dynamic performance and reliability of the low-cost, open-access quadruped robot Solo-12, which is developed within the framework of Open Dynamic Robot Initiative. It presents the implementation of a state-of-the-art control pipeline, close to the one that was previously implemented on Mini Cheetah, which implements a model predictive controller based on the centroid... |
Imitation Learning from MPC for Quadrupedal Multi-Gait Control | https://ieeexplore.ieee.org/document/9561444/ | [
"Alexander Reske",
"Jan Carius",
"Yuntao Ma",
"Farbod Farshidian",
"Marco Hutter",
"Alexander Reske",
"Jan Carius",
"Yuntao Ma",
"Farbod Farshidian",
"Marco Hutter"
] | We present a learning algorithm for training a single policy that imitates multiple gaits of a walking robot. To achieve this, we use and extend MPC-Net, which is an Imitation Learning approach guided by Model Predictive Control (MPC). The strategy of MPC-Net differs from many other approaches since its objective is to minimize the control Hamiltonian, which derives from the principle of optimalit... |
Comparison of predictive controllers for locomotion and balance recovery of quadruped robots | https://ieeexplore.ieee.org/document/9560976/ | [
"Thomas Corbères",
"Thomas Flayols",
"Pierre-Alexandre Léziart",
"Rohan Budhiraja",
"Philippe Souères",
"Guilhem Saurel",
"Nicolas Mansard",
"Thomas Corbères",
"Thomas Flayols",
"Pierre-Alexandre Léziart",
"Rohan Budhiraja",
"Philippe Souères",
"Guilhem Saurel",
"Nicolas Mansard"
] | As locomotion decisions must be taken by considering the future, most existing quadruped controllers are based on a model predictive controller (MPC) with a reduced model of the dynamics to generate the motion and a whole- body controller to execute it. Yet the simplifying assumptions of the MPC are often chosen ad-hoc or by intuition. In this article, we focus on a set of MPCs and analyze the eff... |
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