This paper proposes a novel obstacle-crossing method for wheeled bipedal robots with specialized leg configurations, addressing the limitations of existing jumping-based approaches that suffer from high landing impacts, suboptimal jump heights, and extreme demands on joint torque/battery discharge. Experimenter first derive the robot's dynamics model and establish an Obstacle-Climbing Wheeled Inverted Pendulum (OCWIP) model corresponding to the asymmetric five-bar linkage mechanism, replacing spring forces with virtual forces. Trajectory planning synchronized with body-wheel motion is then implemented based on the OCWIP model, dividing obstacle-crossing into three phases for dynamic analysis. Compared to jumping methods, our approach utilizes passive body tilting followed by leg retraction to ascend steps, significantly reducing mechanical shock on leg structures and extending the lifespan of actuators/batteries. A hierarchical controller integrates leg motion, aerial attitude adjustment, and trajectory tracking to achieve real-time stabilization and robust execution. Experimental validation demonstrates >90% success rate on a physical platform. Key contributions are: 1) A GPU-accelerated solver for optimal linkage combination; 2) Development of the asymmetric five-bar OCWIP model; 3) Hardware validation of the obstacle-crossing framework.
Z. Cen (Tue,) studied this question.