Grasp feasibility computation based on cascading filters. application to a three fingered gripper

A simple, yet effective approach to grasp feasibility analysis is presented. The goal is to reduce the computational complexity of such process, whose complexity makes the detection of all feasible grasps for a certain object unavoidable in most occasions. The approach is based on cascading filters of increasing complexity. First, trivial filters are applied to all the grasp examples, thus rejecting all clearly unfeasible grasps with a small computational effort. Then, more complex filters are applied to a reduced number of grasps and, at the end, the full kinematics and collision detection analysis is only performed with a small subset of the grasps. An example application is presented, where the goal is to detect all the possible 2D grasps of a certain object with an articulated three-fingered hand attached to a scara robot. The vertical axis is decoupled, thus resulting in a highly redundant 7 DOF planar device. Simulation results are presented, where the reduction in computational complexity is evaluated in terms of the number of floating point operations required. Such reduction can be as high as 97% of the original computation time. An experimental setup has also been developed, with an industrial scara robot and a specifically designed articulated three-fingered gripper. The gripper has pneumatically actuated opening and closing of the fingers and electrically actuated abduction of the articulated fingers. In such experimental setup, the cascading filters approach shows a good behavior. Besides, the proposed system can be easily adapted to different robot arms and hands.