Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers
Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction(2024)
摘要
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.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要