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Customized grippers have broad applications in industrial assembly lines.Compared with general parallel grippers, the customized grippers havespecifically designed fingers to increase the contact area with the workpiecesand improve the grasp robustness. However, grasp planning for customizedgrippers is challenging due to the object variations, surface contacts andstructural constraints of the grippers. In this paper, an iterative surfacefitting (ISF) algorithm is proposed to plan grasps for customized grippers. ISFsimultaneously searches for optimal gripper transformation and fingerdisplacement by minimizing the surface fitting error. A guided sampling isintroduced to avoid ISF getting stuck in local optima and improve the collisionavoidance performance. The proposed algorithm is able to consider thestructural constraints of the gripper and plan optimal grasps in real-time. Theeffectiveness of the algorithm is verified by both simulations and experiments.The experimental videos are available at:http://me.berkeley.edu/\%7Eyongxiangfan/CASE2018/caseisf.html

Grasp Planning for Customized Grippers by Iterative Surface Fitting