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

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 body-environment dynamics.