A hyper-redundant robotic arm is a manipulator with many degrees of freedom, capable of executing tasks in cluttered environments where robotic arms with fewer degrees of freedom are unable to operate. This paper introduces a new method for modeling those manipulators in a completely dynamic way. The proposed method enables online changes of the kinematic structure with the use of a special function; termed “meta-controlling function”. This function can be used to develop policies to reduce drastically the computational cost for a single task, and to robustly control the robotic arm, even in the event of partial damage. The direct and inverse kinematics are solved for a generic three-dimensional articulated hyperredundant arm, that can be used as a proof of concept for more specific structures. To demonstrate the robustness of our method, experimental simulation results, for a basic “meta-controlling” function, are presented.
Adaptation to partial failure is one of the most important requirements for space robotics, since space robots cannot be repaired after they have been launched. We propose a decentralized autonomous control algorithm for hyper-redundant manipulators that uses parallel processing with low-performance processors to achieve this adaptation. In this paper, a number of manipulator joints are locked at a certain angle in a computer simulation and the adaptability of the control algorithm to these failures is assessed. The control algorithm successfully continues its positioning task at a rate of more than 90 , even after half of its joints have failed. The control algorithm is also compared with behavior-based control architecture.