Real-Time Grasp Planning for Multi-Fingered Hands by Finger Splitting

TL;DR

This paper introduces a real-time grasp planning method for multi-fingered robotic hands using finger splitting, which efficiently optimizes contact points and palm pose through dual-stage iterative optimization, enabling practical applications.

Contribution

It proposes a novel finger splitting strategy with dual-stage optimization to enable real-time grasp planning for complex multi-fingered hands.

Findings

Achieves convergence within one second.

Effectively considers grasp quality and manipulability.

Demonstrates success in simulation results.

Abstract

Grasp planning for multi-fingered hands is computationally expensive due to the joint-contact coupling, surface nonlinearities and high dimensionality, thus is generally not affordable for real-time implementations. Traditional planning methods by optimization, sampling or learning work well in planning for parallel grippers but remain challenging for multi-fingered hands. This paper proposes a strategy called finger splitting, to plan precision grasps for multi-fingered hands starting from optimal parallel grasps. The finger splitting is optimized by a dual-stage iterative optimization including a contact point optimization (CPO) and a palm pose optimization (PPO), to gradually split fingers and adjust both the contact points and the palm pose. The dual-stage optimization is able to consider both the object grasp quality and hand manipulability, address the nonlinearities and coupling, and achieve efficient convergence within one second. Simulation results demonstrate the effectiveness of the proposed approach. The simulation video is available at: http://me.berkeley.edu/\%7Eyongxiangfan/IROS2018/fingersplit.html