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

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