CPG-based locomotion control of a snake-like robot for obstacle avoidance

Abstract

This paper presents a biomimetic approach based on central pattern generator (CPG), to control turning motion of a snake-like robot. One of the interesting features of a biological snake is its ability to avoid obstacles or a barrier by turning its whole body from its trajectory. This special obstacle avoidance motion is different from other types of animal, and thus, it is worth to be analyzed and realized into a snake-like robot. The paper first briefly explains: 1) the phase oscillator model which represents the CPG model and 2) the CPG network. Next, we address several issues related to the existing/typical turning control of a snake-like robot. We then propose the phase transition method utilizing the phase difference control parameter to realize the turning motion of a snake-like robot. We also introduce a new parameter to control the turning of the robot, where it provides a way to incorporate sensory feedback into the CPG model. Simulation results show that the proposed turning method can be used efficiently as an obstacle avoidance method for a snake-like robot.

Collaborative robots (cobots) for disaster risk resilience: a framework for swarm of snake robots in delivering first aid in emergency situations

“…This approach involves creating an artificial field around objects, and the robot’s motion is designed to avoid this force field. Another algorithm utilised in snake robot locomotion is the central pattern generator (CPG), mentioned by Nor and Ma (2014) . CPG enables the robot to navigate around obstacles or barriers by adjusting the turning of its body from its intended trajectory.…”

A Survey on Snake Robot Locomotion

“…In [64], a hybrid control methodology by integrating APF with a modified Simulated Annealing (SA) optimization algorithm is proposed to avoid local minima. Another algorithm known as the Central Pattern Generator (CPG) [65] allow the robot to avoid obstacles or barriers by turning the robot body from its trajectory. The CPG model also allows collision detection using sensory feedback.…”

Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities †

“…To escape local minima, a hybrid control methodology using APF integrated with a modified simulated annealing (SA) optimization algorithm for motion planning of a team of multi-link snake robots was proposed in [34]. An alternative methodology was developed in [35]. Central pattern generators (CPGs) were employed to allow the robot to avoid obstacles or barriers by turning the robot's body from its trajectory.…”