Research on Omnidirectional Gait Switching and Attitude Control in Hexapod Robots

Area of Science:

• Robotics
• Control Systems
• Artificial Intelligence

Background:

• Hexapod robots face challenges in real-time gait switching and precise trajectory control, especially under limited movement conditions.
• Existing methods struggle with stability during gait transitions and precise path following.

Purpose of the Study:

• To develop a novel real-time replanning gait switching control strategy for hexapod robots.
• To enhance the stability and trajectory control capabilities of hexapod robots in complex environments.
• To address limitations in stride and steering for improved robotic locomotion.

Main Methods:

• Developed a hexapod robot kinematic model using Denavit-Hartenberg (D-H) analysis.
• Implemented a real-time replanning gait switching strategy utilizing an omnidirectional gait and fuzzy inference.
• Applied a single-neuron adaptive proportional-integral-derivative (PID) controller for attitude adjustment.

Main Results:

• The proposed strategy enables seamless, real-time gait switching for hexapod robots.
• Achieved precise trajectory control under limited stride and steering conditions.
• Significantly improved the dynamic stability and adaptability of the hexapod robot in complex terrains.

Conclusions:

• The novel control strategy effectively enhances hexapod robot performance in terms of stability and control.
• The integrated approach of omnidirectional gait, fuzzy inference, and adaptive PID control offers a robust solution for robotic locomotion.
• This research contributes to advancing the capabilities of hexapod robots for navigating challenging and dynamic environments.