A self organization approach to goal-directed multimodal locomotion based on Attractor Selection Mechanism

Abstract

The realization and utilization of multimodal locomotion to enable robots to accomplish useful tasks is a significantly challenging problem in robotics. Related to the challenge, it is crucial to notice that the locomotion dynamics of the robots is a result of interactions between a particular control structure and its body-environment dynamics. From this perspective, this paper presents a simple control structure known as Attractor Selection Mechanism that enables a robot to self organize its multiple locomotion modes for accomplishing a goal-directed locomotion task. Despite the simplicity, the approach enables the robot to automatically explore different body-environment dynamics and stabilize onto particular attractors which corresponds to locomotion modes relevant to accomplish the task. The robot used throughout the paper is a curved-beam hopping robot, which despite its simple actuation method, possesses rich and complex bodyenvironment dynamics.

Muscle Coordination Control for an Asymmetrically Antagonistic-Driven Musculoskeletal Robot Using Attractor Selection

“…This adaptive behavior of the E. coli cells is known as attractor selection [ 12 ]. The novel control method based on the attractor selection has been proposed and applied to a signal-control method for traffic networks [ 13 ], network management [ 14 , 15 ], android motion generation [ 16 ], robot navigation and locomotion [ 17 – 19 ], robotic arm control [ 20 – 22 ], and endoscopic surgery [ 23 ].…”