Planning and Control for Wheel-Leg Hybrid Locomotion in Wheeled Biped Robots for Obstacle Traversal

This paper presents a wheel-leg hybrid gait planning and whole-body motion generation method for wheeled biped robots (WBR). This method utilizes momentum to evaluate the robot’s balance, and employs direct collocation to optimized generation the wheel-leg hybrid gait in real-time based on the environment elevation information. The trajectory optimization (TO) is decoupled into the forward and lateral motion to reduce the solution time for each subproblem, thereby enhancing the efficiency of the overall planning, enabling online trajectory generation at 5 Hz. An obstacle search algorithm is proposed to identify the obstacles along the robot’s reference path and construct terrain and safety constraints, which are incorporated into the optimization problem through exponential control barrier function. This facilitates the online generation of the robot’s contact sequence, ensuring that wheels movement remain within a safe region. Finally, a balance and trajectory tracking controller based on nonlinear model predictive control (NMPC) is proposed to generate the CoM’s spatial motion and contact trajectory at a higher update frequency (200Hz), which are then mapped into the joint space using inverse kinematic, enabling the robot to track the reference gait trajectory while maintaining balance. Experimental validation on a hydraulically driven WBR demonstrates that the method enables periodic hybrid gait generation and real-time obstacle search and traversal. Note to Practitioners—The wheeled-legged robot combines the speed and efficiency of wheeled robots with the terrain traversal capabilities of legged robots, making it an ideal solution for mobile robots operating in challenging terrains. However, the wheeled biped robots, as a subclass of wheeled-legged robot, possesses under-actuated and inherently unstable characteristics, current motion control research for such robots mainly focuses on rolling control. When obstacles are present along the robot’s motion path, it is necessary to re-plan the trajectory to avoid collision, which will reduce the robot’s operational efficiency in real-world environments. Therefore, the motivation of this paper is to develop a wheel-leg hybrid gait planning and control method for WBRs, enabling the robot to identify obstacles along the motion path based on terrain information and generate hybrid gaits on-line to traverse the obstacles. This approach holds significant practical implications for enhancing the robot’s terrain adaptability and operational efficiency.