![]() Common practical methods in the area suffer from inaccurate ergonomics models in performing postural optimization. Defining an accurate and easy-to-use ergonomic assessment model stands as an important step in providing feedback for postural correction to improve operator health and comfort. Keywords: Physical Human-Robot Interaction, Safety in HRI, Human-Aware Motion PlanningĪbstract: Ergonomics and human comfort are essential concerns in physical human-robot interaction applications. Results of an online user study with 125 participants demonstrate that our framework improves the task performance and collaborative fluency of human-agent teams, as compared to state of the art reinforcement learning methods.ĭULA and DEBA: Differentiable Ergonomic Risk Models for Postural Assessment and Optimization in Ergonomically Intelligent PHRI We evaluate our model on a collaborative cooking task using an Overcooked simulator. Robot policies are learned on each of the identified strategies to construct a Mixture-of-Experts model that adapts to the task strategies of unseen human partners. ![]() By transforming team actions into low dimensional representations using hidden Markov models, we can identify strategies without prior knowledge. We first present an algorithm for autonomously recognizing available task-completion strategies by observing human-human teams performing a collaborative task. Our goal in this work is to develop a computational framework for robot adaptation to human partners in human-robot team collaborations. ![]() Robots designed for such collaboration must reason about how their task-completion strategies interplay with the behavior and skills of their human team members as they coordinate on achieving joint goals. ![]() Keywords: Human-Robot Collaboration, Human-Robot TeamingĪbstract: Human and robot partners increasingly need to work together to perform tasks as a team. ![]()
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