Implementation and Control of a Wheeled Bipedal Robot Using a Fuzzy Logic Approach

被引:3
作者
Hsu, Chun-Fei [1 ]
Chen, Bo-Rui [2 ]
Lin, Zi-Ling [1 ]
机构
[1] Tamkang Univ, Dept Elect Engn, 151 Yingzhuan Rd, New Taipei City 25137, Taiwan
[2] Natl Yang Ming Chiao Tung Univ, Inst Elect & Control Engn, Dept Elect & Comp Engn, Hsinchu 30010, Taiwan
关键词
fuzzy control; balance control; movement control; wheeled bipedal robot; TRAJECTORY OPTIMIZATION; BALANCE CONTROL; DESIGN; SPEED;
D O I
10.3390/act11120357
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This study designs and implements a wheeled bipedal robot (WBR) that combines the mobility of wheeled robots and the dexterity of legged robots. The designed WBR has extra knee joints to maintain body balance when encountering uneven terrain. Because of the robot's highly nonlinear, dynamic, unstable, and under-actuated nature, an intelligent motion and balance controller (IMBC) based on a fuzzy logic approach is proposed to maintain the balance of the WBR while it is standing and moving on the ground. It should be emphasized that the proposed IMBC system does not require prior knowledge of system dynamics and the controller parameters are tuned using the qualitative aspects of human knowledge. Furthermore, a 32-bit microcontroller that has memory, programmable I/O peripherals, and a processor core is used to implement the IMBC method. Finally, moving and rotating, height-changing, posture-keeping, and "one leg on slope" movement scenarios are tested to demonstrate the feasibility of the proposed IMBC system. The experimental results show that, by using the proposed IMBC system, the WBR can not only balance and move well both on flat ground and in complex terrain but also extend each leg independently to maintain body balance.
引用
收藏
页数:17
相关论文
共 48 条
[11]   Design and Control of TAWL-A Wheel-Legged Rover With Terrain-Adaptive Wheel Speed Allocation Capability [J].
He, Jun ;
Sun, Yanlong ;
Yang, Limin ;
Sun, Jiaze ;
Xing, Yan ;
Gao, Feng .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2022, 27 (04) :2212-2223
[12]   Double-loop fuzzy motion control with CoG supervisor for two-wheeled self-balancing assistant robots [J].
Hsu C.-F. ;
Kao W.-F. .
International Journal of Dynamics and Control, 2020, 8 (03) :851-866
[13]   Perturbation wavelet neural sliding mode position control for a voice coil motor driver [J].
Hsu, Chun-Fei ;
Kao, Wei-Fu .
NEURAL COMPUTING & APPLICATIONS, 2019, 31 (10) :5975-5988
[14]   Interval Type-2 Fuzzy Logic Modeling and Control of a Mobile Two-Wheeled Inverted Pendulum [J].
Huang, Jian ;
Ri, MyongHyok ;
Wu, Dongrui ;
Ri, Songhyok .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (04) :2030-2038
[15]   Robust Navigational Control of a Two-Wheeled Self-Balancing Robot in a Sensed Environment [J].
Iwendi, Celestine ;
Alqarni, Mohammed A. ;
Anajemba, Joseph Henry ;
Alfakeeh, Ahmed S. ;
Zhang, Zhiyong ;
Bashir, Ali Kashif .
IEEE ACCESS, 2019, 7 :82337-82348
[16]   LQR-Assisted Whole-Body Control of a Wheeled Bipedal Robot With Kinematic Loops [J].
Klemm, Victor ;
Morra, Alessandro ;
Gulich, Lionel ;
Mannhart, Dominik ;
Rohr, David ;
Kamel, Mina ;
de Viragh, Yvain ;
Siegwart, Roland .
IEEE ROBOTICS AND AUTOMATION LETTERS, 2020, 5 (02) :3745-3752
[17]  
Klemm V, 2019, IEEE INT CONF ROBOT, P7515, DOI [10.3929/ethz-b-000384209, 10.1109/ICRA.2019.8793792]
[18]   An efficient and direct method for trajectory optimization of robots constrained by contact kinematics and forces [J].
Lee, Jaemin ;
Bakolas, Efstathios ;
Sentis, Luis .
AUTONOMOUS ROBOTS, 2021, 45 (01) :135-153
[19]   Self-Balancing Two-Wheeled Robot Featuring Intelligent End-to-End Deep Visual-Steering [J].
Li, Chih-Hung Gilbert ;
Zhou, Long-Ping ;
Chao, Yu-Hua .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2021, 26 (05) :2263-2273