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arXiv 2023年

作者： Barot, Pranav Mombaur, Katja MacDonald, Ewen N. Department of Systems Design Engineering University of Waterloo WaterlooON Canada Optimization and Biomechanics for Human-Centred Robotics Karlsruhe Germany and CERC Human-Centred Robotics and Machine Intelligence Department of Systems Design Engineering University of Waterloo Waterloo Canada

To achieve human-like behaviour during speech interactions, it is necessary for a humanoid robot to estimate the location of a human talker. Here, we present a method to optimize the parameters used for the direction of arrival (DOA) estimation, while also considering real-time applications for human-robot interaction scenarios. This method is applied to binaural sound source localization framework on a humanoid robotic head. Real data is collected and annotated for this work. Optimizations are performed via a brute force method and a Bayesian model based method, results are validated and discussed, and effects on latency for real-time use are also explored. © 2023, CC BY.

关键词： Anthropomorphic robots

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A Bio-inspired Solution for Double Support Force Distribution in humanoid Robot Locomotion

A Bio-inspired Solution for Double Support Force Distributio...

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IEEE-RAS International Conference on humanoid Robots

作者： Francisco Javier Andrade Chavez Vidyasagar Rajendran Katja Mombaur CERC Human-Centred Robotics and Machine Intelligence of Department of Systems Design Engineering University of Waterloo Canada Optimization and Biomechanics for Human-Centred Robotics Karlsruhe Institute of Technology (KIT) Institute of Anthropomatics and Robotics (IAR) Karlsruhe Germany

In locomotion, the likelihood of slipping or maintaining contact is determined by the forces applied in the environment. Therefore, it is crucial to find methods of keeping forces within friction constraints. In single support, the relationship between center of mass acceleration and forces is unique. However, in double support, it becomes a non-deterministic problem. It is often assumed that forces are distributed to minimize a certain effort criterion. An interesting alternative is to distribute the forces in a manner similar to how a human would, which could result in a more human-like gait for humanoid robots. With this in mind, we introduce the modified Twin Polynomial Method (mTPM) as a technique to accurately distribute double support forces in a human-like way. The relevant relationships used in this method are presented, and we compare its performance against the current state of the art in human gait analysis. The comparison is conducted across three different types of contacts with the environment: barefoot, socks, and shoes. We show how human data differs from a ‘typical’ robot walk and use the proposed method to generate a more human-like distribution for robots.

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Whole-body Stabilization of the REEM-C humanoid on Actuated Balance Boards in Sagittal and Frontal Directions

Whole-body Stabilization of the REEM-C Humanoid on Actuated ...

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IEEE-RAS International Conference on humanoid Robots

作者： Vidyasagar Rajendran Francisco Javier Andrade Chavez Katja Mombaur Department of Systems Design Engineering CERC Human-Centred Robotics and Machine Intelligence University Waterloo Canada Optimization and Biomechanics for Human-Centred Robotics Institute of Anthropomatics and Robotics (IAR) Karlsruhe Institute of Technology (KIT) Karlsruhe Canada

This paper explores stabilizer design for humanoid balancing on actuated balance boards. We qualitatively study how humans balance on balance boards to motivate our humanoid controller design. The developed approach combines various strategies from the literature including ankle admittance, CoM admittance, base pitch admittance, foot force difference admittance, contact wrench distribution and angular momentum regulation in a new integration to achieve stabilization on an actuated balance board. We explore the frontal and sagittal plane balance board problems along with pushes at the upper body and show that our approach works in simulation and on real hardware. This brings us one step closer to balancing on unactuated balance boards, other dynamic environments such as moving platforms and transportation devices, skills that will make humanoids more versatile.

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An Audio-Video Sensor Fusion Framework To Augment humanoid Capabilities For Identifying And Interacting With human Conversational Partners

An Audio-Video Sensor Fusion Framework To Augment Humanoid C...

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IEEE-RAS International Conference on humanoid Robots

作者： Pranav Barot Ewen N. MacDonald Katja Mombaur Department of Systems Design Engineering University of Waterloo Canada Department of Systems Design Engineering University of Waterloo Optimization and Biomechanics for Human-Centred Robotics Karlsruhe Germany and CERC Human-Centred Robotics and Machine Intelligence Karlsruhe Institute of Technology (KIT) Institute of Anthropomatics and Robotics (IAR) Waterloo Canada

human robot interaction often requires many sub-systems to work together in order to facilitate more natural and intelligent interactions with multiple humans. For this work, the relevant systems include audio and visual direction of arrival estimation that are used in an encompassing sensor fusion framework. The presented sub-systems are used concurrently online to allow for humanoid robots to identify active speakers in a scene, track human subjects, and identify when other subjects may require attention. We present evaluations of performance, while also implementing relevant humanlike behaviours on the REEM-C humanoid Robot. A conducted user study delivers valuable feedback on these systems, which provide a strong foundation for improved humanoid intelligence and more innovative human-robot interaction.

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Learning Skateboarding for humanoid Robots through Massively Parallel Reinforcement Learning

arXiv

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arXiv 2024年

作者： Thibault, William Rajendran, Vidyasagar Melek, William Mombaur, Katja Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada The Department of Systems Design Engineering CERC Human-Centred Robotics and Machine Intelligence University of Waterloo Canada Karlsruhe Germany

Learning-based methods have proven useful at generating complex motions for robots, including humanoids. Reinforcement learning (RL) has been used to learn locomotion policies, some of which leverage a periodic reward formulation. This work extends the periodic reward formulation of locomotion to skateboarding for the REEM-C robot. Brax/MJX is used to implement the RL problem to achieve fast training. Initial results in simulation are presented with hardware experiments in progress. © 2024, CC BY.

关键词： Reinforcement learning

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Optimization and Evaluation of Spinal Exoskeleton design Concepts using Optimal Control 10th

Optimization and Evaluation of Spinal Exoskeleton Design Con...

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10th ECCOMAS Multibody Conference 2021

作者： Harant, Monika Näf, Matthias B. Mombaur, Katja Mathematics for the Digital Factory Fraunhofer Intitute for Industrial Mathematics Fraunhofer-Platz 1 Kaiserslautern67663 Germany Department of Mechanical Engineering Vrije Universiteit Brussel Pleinlaan 2 Brussels1050 Belgium CERC Human-Centred Robotics and Machine Intelligence University of Waterloo 200 University Avenue West WaterlooN2L 3G1 Canada

ISBN: (纸本)9789634218708

Exoskeletons for the lower back are promising tools to support workers during heavy lifting tasks. Their development process faces several challenges. It is still not known which criteria the support must meet to prevent low-back pain and how users of different body stature and execution of lifting movements influence it. Thus, studying these factors needs an extensive testing on the human body and every considered design concept needs already a sophisticated prototype that subjects can wear for several hours. To overcome this issue, we propose a method using multibody dynamics and optimal control to optimize the design of an existing prototype (PO) as well as evaluate a new concept (DC) that incorporates motors at the hip joint. A dynamic model of the prototype with matching torque generation was developed, which also takes an approximation of possible misalignment into account. The human-robot interaction is simulated in an all-at-once approach that allows to calculate the muscle activity of the user required in addition to the exoskeleton support to reproduce recorded lifting motions. By minimizing the users’ muscle activity, parameters describing the characteristics of the passive elements and, in case of DC, motor torque profiles are optimized. Compared to the initial setup, a significant improvement in exoskeletal support was achieved across all subjects in both cases while contact forces remained within prescribed limits to ensure a comfortable usage of the device. DC provides less support than PO but better control of the human-robot interaction. © 2021, Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics. All rights reserved.

关键词： human robot interaction

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