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.
|Title of host publication||Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2020|
|Place of Publication||Piscataway, NJ, USA|
|Publication status||Published - 2020|
|Event||2020 IEEE International Conference on Robotics and Automation, ICRA 2020 - Paris, France|
Duration: 31 May 2020 → 31 Aug 2020
|Conference||2020 IEEE International Conference on Robotics and Automation, ICRA 2020|
|Period||31/05/20 → 31/08/20|