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.

六足机器人是有腿机器人中的重要类别之一，因为它具有在复杂环境中以高稳定性和灵活性进行操作的巨大潜力。然而，很少有研究调查这种类型的机器人的导航和自主运动。本文涉及利用混合自动机的自主六足机器人的基于行为的控制和导航。不同行为之间的切换是基于感官数据的，并且不包括环境的表示。由于这些系统可能会出现颤动现象，因此在目标吸引和避障模式之间考虑了包括顺时针和逆时针边界跟随行为的滑动模式，以修改自动机。混合自动机代替机器人进行参考点的路径规划。因此，为了能够实现导航算法，六足机器人在两次转换后被转换为点质量机器人。还进行了参数研究，以研究控制器设计参数对导航算法和机器人性能的影响。结果表明，增强机器人运动的平稳性会降低跟踪参考点和反应速度的精度，反之亦然。此外，仿真测试通过完美地在不同模式之间切换以及机器人以任意步态跟随参考点的能力，证实了导航算法在生成最佳路径方面的有效性。此外，将本文介绍的导航策略的性能与类似算法的性能进行了比较，