Bimanual handovers are crucial for transferring large, deformable or delicate objects. This paper proposes a framework for generating kinematically constrained human-like bimanual robot motions to ensure seamless and natural robot-to-human object handovers. We use a Hidden Semi-Markov Model (HSMM) to reactively generate suitable response trajectories for a robot based on the observed human partner's motion. The trajectories are adapted with task space constraints to ensure accurate handovers. Results from a pilot study show that our approach is perceived as more human--like compared to a baseline Inverse Kinematics approach.
@article{arxiv.2402.14525,
title = {Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers},
author = {Yasemin Göksu and Antonio De Almeida Correia and Vignesh Prasad and Alap Kshirsagar and Dorothea Koert and Jan Peters and Georgia Chalvatzaki},
journal= {arXiv preprint arXiv:2402.14525},
year = {2024}
}
Comments
Accepted as a Late Breaking Report in The ACM/IEEE International Conference on Human Robot Interaction (HRI) 2024