Bo Hu and Xueli Wang
Quadruped robot, stair terrain, motion control, posture adjustment,virtual slope
To promote the development and application of intelligent robots, this study explores the motion posture and torso adjustment of robots. Combining predictive control and whole-body control, the motion posture of the quadruped robot is controlled and adjusted. The adaptive adjustment algorithm and visual technology are used to improve the motion control of the climbing robot. According to the simulation results, the error rate of the quadruped robot’s ground walking was 7.14% during the adaptive walking process from horizontal to slope. In addition, under the model predictive control and climbing planning, the average pitch angle of the robot walking on stairs was 0.36 rad, and the error rate of walking on slopes was 5.42%, meeting the requirements for stable motion of quadruped robots in complex terrain. Therefore, it demonstrates the superiority of the vision-based stable climbing algorithm for quadruped robots, and provides service technology for future intelligent autonomous operation of robots.
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