Abstract

The development of flexible multifingered grippers with both adaptive grasping and in-hand manipulation capabilities remains a complex issue for human-like dexterous manipulation. After four decades of research in dexterous manipulation, many robotic hands have been developed. The development of these hands remains a key challenge, as the dexterity of robot hands is far from human capabilities. Through the evolution of robotics (from industrial and manufacturing robotics to service and collaborative robotics), the monograph details the evolution of the grasping function (from industrial grippers to dexterous robot hands) and the stakes inherent today to new robotic applications in open, dynamic environments. The aim of the monograph is to assist in the choice of a grasping and manipulation solution, taking into account both the design and control aspects, from the simplest industrial gripper to the most sophisticated multidigital hands. The increasing complexity of grasping function to meet flexibility challenges led to the development of control strategies based on theoretical approaches and data-based approaches using machine learning.