Real-Time Finger Gaits Planning for Dexterous Manipulation

Abstract

Dexterous manipulation has broad potential applications in assembly lines, warehouses and agriculture, and so on. To perform large-scale, complicated manipulation tasks, a multi-fingered robotic hand sometimes has to sequentially adjust its grasping status, i.e. the finger gaits, to deal with the workspace limits and object stability. However, realizing finger gaits planning in dexterous manipulation is challenging due to the involved hybrid dynamics, complicated grasp quality metrics, and uncertainties during the finger gaiting. In this paper, a dual-stage optimization based controller is proposed to handle these challenges. First, a velocity-level finger gaits planner is introduced by combining object grasp quality with hand kinematic limitations. The proposed finger gaits planner is computationally efficient and can be solved in real-time. Second, a manipulation controller using force optimization is presented. To deal with mass uncertainties and external disturbances, a modified impedance control is integrated into the manipulation controller. The dual-stage controller does not require the shape of the object, nor does it rely on expensive 3D/6D tactile sensors. Simulation results verify the efficacy of the proposed dual-stage controller.