Predicting and Optimizing Ergonomics in Physical Human-Robot Cooperation Tasks
| Autor: | Tamas Bates, Michael Gienger, Jens Kober, Linda F. van der Spaa |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
020901 industrial engineering & automation Computer science Human–computer interaction 05 social sciences Human factors and ergonomics 0501 psychology and cognitive sciences Mobile robot 02 engineering and technology Object (computer science) 050107 human factors Human–robot interaction Task (project management) |
| Zdroj: | Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2020 ICRA |
| DOI: | 10.1109/icra40945.2020.9197296 |
| Popis: | This paper presents a method to incorporate ergonomics into the optimization of action sequences for bi-manual human-robot cooperation tasks with continuous physical interaction. Our first contribution is a novel computational model of the human that allows prediction of an ergonomics assessment corresponding to each step in a task. The model is learned from human motion capture data in order to predict the human pose as realistically as possible. The second contribution is a combination of this prediction model with an informed graph search algorithm, which allows computation of human-robot cooperative plans with improved ergonomics according to the incorporated method for ergonomic assessment. The concepts have been evaluated in simulation and in a small user study in which the subjects manipulate a large object with a 32 DoF bimanual mobile robot as partner. For all subjects, the ergonomic-enhanced planner shows their reduced ergonomic cost compared to a baseline planner. |
| Databáze: | OpenAIRE |
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