Efficient modular grasping: An iterative approach

Abstract

This paper introduces a new modular approach to robotic grasping that allows for finding a trade off between a simple gripper and more complex human like manipulators. The modular approach to robotic grasping aims to understand human grasping behavior in order to replicate grasping and skilled in-hand movements with an artificial hand using simple, robust, and flexible modules. In this work, the design of modular grasping devices capable of adapting to different requirements and situations is investigated. A novel algorithm that determines effective modular configurations to get efficient grasps of given objects is presented. The resulting modular configurations are able to perform effective grasps that a human would consider “stable”. Related simulations were carried out to validate the efficiency of the algorithm. Preliminary results show the versatility of the modular approach in designing grippers.