Workspace trajectory generation with smooth gait transition using CPG-based locomotion control for hexapod robot

Area of Science:

• Robotics
• Control Systems
• Bio-inspired Engineering

Background:

• Legged robots require adaptable locomotion for diverse terrains.
• Smooth gait transitions are crucial for stable and efficient movement.
• Central Pattern Generators (CPGs) offer a bio-inspired approach to robotic locomotion control.

Purpose of the Study:

• To develop a control methodology for smooth gait transitions in hexapod robots.
• To enhance the adaptability of hexapod robots to changing environmental conditions.
• To enable online adjustment of foot trajectory parameters for dynamic locomotion control.

Main Methods:

• Modification of the Phase Oscillator within the CPG network.
• Design of a foot trajectory generator based on CPG output.
• Simulation and experimental validation on a hexapod robot.

Main Results:

• Achieved significantly smoother gait transitions with reduced transition times.
• Demonstrated the feasibility of online adjustment for step height, size, speed, and direction.
• Validated the effectiveness of the modified CPG approach in simulations and real-world experiments.

Conclusions:

• The proposed CPG-based control methodology effectively enables smooth gait transitions in hexapod robots.
• Online adjustability of trajectory parameters enhances the robot's adaptability and navigation capabilities.
• This approach holds significant potential for advancing legged robot locomotion in complex terrains.