Behavior-Based Navigation of an Autonomous Hexapod Robot Using a Hybrid Automaton

Abstract

The hexapod robot is one of the important classes in legged robots due to its great potential to operate in complex settings with high stability and flexibility. However, few researches have investigated the navigation and autonomous locomotion of this type of robot. This paper concerns with the behavior-based control and navigation of an autonomous hexapod robot utilizing a hybrid automaton. Switching between the distinct behaviors is based on the sensory data, and no representation of the environment is included. Since these systems are likely to rise chattering phenomenon, a sliding mode including clockwise and counter-clockwise boundary following behaviors are considered between the goal attraction and obstacle avoidance modes to modify the automaton. The hybrid automaton undertakes the path planning of a reference point instead of the robot. Thus, in order to be able to implement the navigation algorithm, the hexapod robot is converted to a point mass robot within two transformations. A parameter study is also performed to investigate the effects of the controllers’ design parameters on the performance of the navigation algorithm and robot. The results show that enhancing the smoothness of the robot’s motion would deteriorate the precision in tracking the reference point and the reaction speed and vice versa. Moreover, simulation tests confirm the effectiveness of the navigation algorithm in generating the optimal path by perfectly switching between distinct modes as well as the capability of the robot to follow the reference point with an arbitrary gait. Furthermore, comparing the performance of the presented navigation strategy to that of similar algorithms, such as Bug and Potential field, yields a satisfying result.