Sampling-based finger gaits planning for multifingered robotic hand

To perform large scale or complicated manipulation tasks, a multi-fingered robotic hand sometimes has to sequentially adjust its grasp status to overcome constraints of the manipulation, such as workspace limits, force balance requirement, etc. Such a strategy of changing grasping status is called a finger gait, which exhibits strong hybrid characteristics due to the discontinuity caused by relocating limited fingers and the continuity caused by manipulating objects. This paper aims to explore the complicated finger gaits planning problem and provide a method for robotic hands to autonomously generate feasible finger gaits to accomplish given tasks. Based on the hybrid automaton formulation of a popular finger gaiting primitive, finger substitution, we formulate the finger gait planning problem into a classic motion planning problem with a hybrid configuration space. Inspired by the rapidly-exploring random tree (RRT) techniques, we develop a finger gait planner to quickly search for a feasible manipulation strategy with finger substitution primitives. To increase the search performance of the planner, we further develop a refined sampling strategy, a novel hybrid distance and an efficient exploring strategy with the consideration of the problem's hybrid nature. Finally, we use a representative numerical example to verify the validity of our problem formulation and the performance of the RRT based finger gait planner.