Adaptive Motion Control of a Terrain-Adaptive Self-Balancing Leg-Wheeled Mobile Robot over Rough Terrain

This paper proposes an adaptive motion control approach that incorporates the backstepping sliding-mode motion control, side tilting control and impedance control method to steer a terrain-adaptive self-balancing leg-wheeled mobile robot over rough and uneven terrain. The proposed robot improves a hybrid design of bipedal walking and wheel-driven modes by adding a new locomotion mechanism. Different from ordinary two-wheeled self-balancing robots, the improved mobile robot has two extra knee joints to keep the body balancing when encountering rough terrain. Because of knee joints, the robot's center of gravity also changes when the robot's posture changes, so motion control of the robot is decomposed into three parts: self-balancing for front tilting, trajectory tracking control, side tilting, and center of gravity (COG), and knees joint's impedance control. In particular, two nonlinear backstepping sliding-mode controllers are proposed to achieve self-balancing, speed tracking and orientation control for the robot moving over flat terrain. The robot's mechatronic design uses a low-level controller with an OpenCR control board and Dynamixel motors, where the OpenCR control board is programmed via Arduino. Simulations and experimental results of the mobile platform traveling around its workspace demonstrate the feasibility and effectiveness of the proposed control strategy.

[1]  Jonghyun Kim,et al.  Impedance Control of Human Ankle Joint With Electrically Stimulated Antagonistic Muscle Co-Contraction , 2021, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[2]  Chenguang Yang,et al.  Optimal Robot–Environment Interaction Under Broad Fuzzy Neural Adaptive Control , 2020, IEEE Transactions on Cybernetics.

[3]  Yili Fu,et al.  Model Decoupling and Control of the Wheeled Humanoid Robot Moving in Sagittal Plane , 2019, 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids).

[4]  Roland Siegwart,et al.  Ascento: A Two-Wheeled Jumping Robot , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[5]  Ching-Chih Tsai,et al.  Trajectory tracking of a self-balancing two-wheeled robot using backstepping sliding-mode control and fuzzy basis function networks , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Ching-Chih Tsai,et al.  Planned navigation of a self-balancing autonomous service robot , 2008, 2008 IEEE Workshop on Advanced robotics and Its Social Impacts.

[7]  A. Shimada,et al.  High-Speed Motion Control of Wheeled Inverted Pendulum Robots , 2007, 2007 IEEE International Conference on Mechatronics.

[8]  Masahito Togami,et al.  Basic Design of Human-Symbiotic Robot EMIEW , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Kaustubh Pathak,et al.  Velocity and position control of a wheeled inverted pendulum by partial feedback linearization , 2005, IEEE Transactions on Robotics.

[10]  Jorge Angeles,et al.  The control of semi-autonomous two-wheeled robots undergoing large payload-variations , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[11]  Roland Siegwart,et al.  Introduction to Autonomous Mobile Robots , 2004 .

[12]  Alfred C. Rufer,et al.  JOE: a mobile, inverted pendulum , 2002, IEEE Trans. Ind. Electron..

[13]  Shin'ichi Yuta,et al.  Trajectory tracking control for navigation of the inverse pendulum type self-contained mobile robot , 1996, Robotics Auton. Syst..