1. Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers
- Author
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Göksu, Yasemin, Correia, Antonio De Almeida, Prasad, Vignesh, Kshirsagar, Alap, Koert, Dorothea, Peters, Jan, and Chalvatzaki, Georgia
- Subjects
Computer Science - Robotics ,Computer Science - Human-Computer Interaction ,Computer Science - Machine Learning - Abstract
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., Comment: Accepted as a Late Breaking Report in The ACM/IEEE International Conference on Human Robot Interaction (HRI) 2024
- Published
- 2024
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