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Robotic grasping of arbitrary objects even in completely known environmentsstill remains a challenging problem. Most previously developed algorithms hadfocused on fingertip grasp, failing to solve the problem even for fullyactuated hands/grippers during adaptive/wrapping type of grasps, where eachfinger makes contact with object at several points. Kinematic closed formsolutions are not possible for such an articulated finger which simultaneouslyreaches several given goal points. This paper, presents a framework forcomputing best grasp for an underactuated robotic gripper, based on a novelobject slicing method. The proposed method quickly find contacts using anobject slicing technique and use grasp quality measure to find the best graspfrom a pool of grasps. To validate the proposed method, implementation has beendone on twenty-four household objects and toys using a two finger underactuatedrobot gripper. Unlike the many other existing approaches, the proposed approachhas several advantages: it can handle objects with complex shapes and sizes; itdoes not require simplifying the objects into primitive geometric shape; Mostimportantly, it can be applied on point clouds taken using depth sensor; ittakes into account gripper kinematic constraints and generates feasible graspsfor both adaptive/enveloping and fingertip types of grasps.

A novel object slicing based grasp planner for 3D object grasping using underactuated robot gripper