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23rd IEEE-RAS International Conference on humanoid Robots, humanoids 2024

作者： Gaebert, Carl Thomas, Ulrike Chemnitz University of Technology Robotics and Human-Machine Interaction Lab Germany

ISBN: (纸本)9798350373578

Solving the Inverse Kinematics Problem is a fundamental skill for humanoid robots and their interaction with the world. In contrast to industrial manipulators, humanoid robots can simultaneously grasp or push objects with two hands. This demands generating self-collision-free inverse kinematics solutions for both arms in a minimal time. Recent research in the context of single-arm manipulators utilizes deep generative models to obtain a whole set of feasible solutions. This paper investigates their performance on the more complex dual-arm problem. To this end, we extend the problem space to a dualarm setup and learn inverse kinematics solutions, providing the two target end effector poses as a conditional variable. We propose an approach based on Conditional Variational Autoencoders and investigate the trade-off between model size, accuracy, and its benefit when being used for seeding a numeric solver. In this context, we also evaluate the influence of flexible learning-based priors against fixed Gaussian priors. Our approach can initialize the solver within 1 ms and drastically increase the number of returned solutions. The results show that even less accurate models can drastically increase the performance of a numeric solver while yielding significantly shorter solving times compared to a state-of-the-art flow-based method. © 2024 IEEE.

关键词： Inverse kinematics

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An Enhanced Walking Pattern Generator with Variable Height for Robot Locomotion 19

An Enhanced Walking Pattern Generator with Variable Height f...

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19th IEEE International Conference on Automation Science and Engineering, CASE 2023

作者： Zhu, Hongxi Thomas, Ulrike Chemnitz University of Technology The Lab of Robotics and Human-Machine-Interaction Chemnitz09126 Germany

ISBN: (纸本)9798350320695

In this paper, we introduce a novel walking pattern generator that builds on the divergent component of motion (DCM) techniques for biped robots. The aim is to provide an efficient algorithm for generating robot footstep position while walking. We build a new biped robot Forrest. For this robot, but also applicable for any biped robot, we developed a new gait pattern generator. Our approach involves utilizing segmented zero moment point (ZMP) curves within each step to generate a smoother desired trajectory. By this way we overcome the issue of abrupt acceleration changes experienced when using traditional walking pattern generators with a constant ZMP. Additionally, our generator employs a 3-D divergent component of motion (DCM) curve to plan for variable heights in the center of mass (CoM) trajectory, which is crucial for achieving a walking pattern that resembles human walking. We introduce this new gait generator and show first result on our biped robot. © 2023 IEEE.

关键词： Acceleration

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Collision Avoidance with Proximity Servoing for Redundant Serial Robot Manipulators

Collision Avoidance with Proximity Servoing for Redundant Se...

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2020 IEEE International Conference on robotics and Automation, ICRA 2020

作者： Ding, Yitao Thomas, Ulrike Chemnitz University of Technology Lab of Robotics and Human Machine-Interaction Chemnitz SN09126 Germany

ISBN: (纸本)9781728173955

Collision avoidance is a key technology towards safe human-robot interaction, especially on-line and fastreacting motions are required. Skins with proximity sensors mounted on the robot's outer shell provide an interesting approach to occlusion-free and low-latency perception. However, collision avoidance algorithms which make extensive use of these properties for fast-reacting motions have not yet been fully investigated. We present an improved collision avoidance algorithm for proximity sensing skins by formulating a quadratic optimization problem with inequality constraints to compute instantaneous optimal joint velocities. Compared to common repulsive force methods, our algorithm confines the approach velocity to obstacles and keeps motions pointing away from obstacles unrestricted. Since with repulsive motions the robot only moves in one direction, opposite to obstacles, our approach has better exploitation of the redundancy space to maintain the task motion and gets stuck less likely in local minima. Furthermore, our method incorporates an active behaviour for avoiding obstacles and evaluates all potentially colliding obstacles for the whole arm, rather than just the single nearest obstacle. We demonstrate the effectiveness of our method with simulations and on real robot manipulators in comparison with commonly used repulsive force methods and our prior proposed approach. © 2020 IEEE.

关键词： Quadratic programming

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A complete automated chain for flexible assembly using recognition, planning and sensor-based execution 47

A complete automated chain for flexible assembly using recog...

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47th International Symposium on robotics, ISR 2016

作者： Nottensteiner, Korbinian Bodenmüller, Tim Kassecker, Michael Roa, Máximo A. Stemmer, Andreas Stouraitis, Theodoros Seidel, Daniel Thomas, Ulrike Germany Sensor Based Robotic Systems and Intelligent Assistance Systems TU Munich Germany Robotics and Human Machine Interaction Lab TU Chemnitz Germany

ISBN: (纸本)9783800742318

This paper presents a fully automated system for automatic assembly of aluminum profile constructions. This high grade of automation of the entire process chain requires novel strategies in recognition, planning and execution. The system includes an assembly sequence planner integrated with a grasp planning tool, a knowledge-based reasoning method, a skill-based code generation, and an error tolerant execution engine. The modular structure of the system allows its adaptation to new products, which can prove especially useful for SMEs producing small lot sizes. The system is robust and stable, as demonstrated with the repeated execution of different geometric assemblies. © 2016 VDE VERLAG GMBH Berlin Offenbach.

关键词： Knowledge based systems

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Maximizing Robot Manipulability along Paths in Collision-free Motion Planning

Maximizing Robot Manipulability along Paths in Collision-fre...

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International Conference on Advanced robotics (ICAR)

作者： Sascha Kaden Ulrike Thomas Robotics and Human-Machine-Interaction Lab Chemnitz University of Technology

A major task in motion planning is to find suitable movements with large manipulability, while collision-free operation must be guaranteed. This condition is increasingly important in the collaboration between humans and robots, as the capability of avoidance to humans or dynamic obstacles must be ensured anytime. For this purpose, paths in motion planning have to be optimized with respect to manipulability and distance to obstacles. Because with a large manipulability the robot has at any time, the possibility of evading due to the greater freedom of movement. Alternatively, the robot can be pushed away by using a Cartesian impedance control. To achieve this, we have developed a combined approach. First, we introduce a Rapidly-exploring Random Tree, which is extended and optimized by state costs for manipulability. Secondly, we perform an optimization using the STOMP method and Gaussian Mixture Models. With this dual approach we are able to find paths in narrow passages and simultaneously optimize the path in terms of manipulability.

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Generating Dual-Arm Inverse Kinematics Solutions using Latent Variable Models

Generating Dual-Arm Inverse Kinematics Solutions using Laten...

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IEEE-RAS International Conference on humanoid Robots

作者： Carl Gaebert Ulrike Thomas Robotics and Human-Machine Interaction Lab Chemnitz University of Technology Germany

ISBN: (数字)9798350373578

ISBN: (纸本)9798350373585

关键词： Accuracy humanoid robots Kinematics End effectors Numerical models Context modeling

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Parameter Optimization for Manipulator Motion Planning using a Novel Benchmark Set

Parameter Optimization for Manipulator Motion Planning using...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Carl Gaebert Sascha Kaden Benjamin Fischer Ulrike Thomas Robotics and Human-Machine Interaction Lab Chemnitz University of Technology Germany

Sampling-based motion planning algorithms have been continuously developed for more than two decades. Apart from mobile robots, they are also widely used in manipulator motion planning. Hence, these methods play a key role in collaborative and shared workspaces. Despite numerous improvements, their performance can highly vary depending on the chosen parameter setting. The optimal parameters depend on numerous factors such as the start state, the goal state and the complexity of the environment. Practitioners usually choose these values using their experience and tedious trial and error experiments. To address this problem, recent works combine hyperparameter optimization methods with motion planning. They show that tuning the planner's parameters can lead to shorter planning times and lower costs. It is not clear, however, how well such approaches generalize to a diverse set of planning problems that include narrow passages as well as barely cluttered environments. In this work, we analyze optimized planner settings for a large set of diverse planning problems. We then provide insights into the connection between the characteristics of the planning problem and the optimal parameters. As a result, we provide a list of recommended parameters for various use-cases. Our experiments are based on a novel motion planning benchmark for manipulators which we provide at https://***/rybj.

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PARAMATER OPTIMIZATION FOR MANIPULATOR MOTION PLANNING USING A NOVEL BENCHMARK SET

arXiv

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arXiv 2023年

作者： Gaebert, Carl Kaden, Sascha Fischer, Benjamin Thomas, Ulrike The Robotics and Human-Machine Interaction Lab Chemnitz University of Technology Germany

关键词： Motion planning

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A New Efficient Eye Gaze Tracker for Robotic Applications

A New Efficient Eye Gaze Tracker for Robotic Applications

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IEEE International Conference on robotics and Automation (ICRA)

作者： Chaitanya Bandi Ulrike Thomas Department of Robotics Human Machine Interaction Lab Technical university of Chemnitz Germany

Gaze estimation provides insight into a person's intent and engagement level, which is helpful in collaborative human-robot applications. With significant advancements in deep learning architectures, appearance-based gaze estimation has gained much attention. Appearance-based methods have shown significant improvement in gaze accuracy and, unlike traditional approaches, they function well in environments where there are no constraints. We present another convolution-based gaze estimation approach to further reduce the angular error. For estimating gaze under extreme conditions such as head variations and distances, full-face images have been shown to be efficient, so we rely on full-face and pay more attention to necessary features. With the proposed architecture, we achieve an accuracy of 3.75° on the MPIIFaceGaze dataset and 3.96° on the ETH-XGaze open-source dataset. In addition, we test eye gaze tracking in real-time robotic applications, such as attention detection, and pick-and-place.

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An Enhanced Walking Pattern Generator with Variable Height for Robot Locomotion

An Enhanced Walking Pattern Generator with Variable Height f...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Hongxi Zhu Ulrike Thomas Lab of Robotics and Human-Machine-Interaction Chemnitz University of Technology Chemnitz Germany

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