Sequential Manipulation Planning for Over-actuated Unmanned Aerial Manipulators

Su, Yao, Li, Jiarui, Jiao, Ziyuan, Wang, Meng, Chu, Chi, Li, Hang, Zhu, Yixin, Liu, Hangxin

arXiv.org Artificial Intelligence 

We investigate the sequential manipulation planning problem for unmanned aerial manipulators (UAMs). Unlike prior work that primarily focuses on one-step manipulation tasks, sequential manipulations require coordinated motions of a UAM's floating base, the manipulator, and the object being manipulated, entailing a unified kinematics and dynamics model for motion planning under designated constraints. By leveraging a virtual kinematic chain (VKC)-based motion planning framework that consolidates components' kinematics into one chain, the sequential manipulation task of a UAM can be planned as a whole, yielding more coordinated motions. Integrating the kinematics and dynamics models with a hierarchical control framework, we demonstrate, for the first time, an over-actuated UAM achieves a series of new sequential manipulation capabilities in both simulation and experiment.

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