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
[1]   Signed-Distance Fuzzy-Logic Sliding-Mode Control Strategy for Floating Interleaved Boost Converter [J].
Benzaouia, Souryane ;
M'Sirdi, Nacer K. ;
Rabhi, Abdelhamid ;
Zouggar, Smail .
2021 9TH INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC'21), 2021, :417-422
[2]  
Chang H.T., 2021, P INT C FUZZY THEORY, P42
[3]  
Chao Zhang, 2019, 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO), P1869, DOI 10.1109/ROBIO49542.2019.8961814
[4]   Underactuated Motion Planning and Control for Jumping With Wheeled-Bipedal Robots [J].
Chen, Hua ;
Wang, Bingheng ;
Hong, Zejun ;
Shen, Cong ;
Wensing, Patrick M. ;
Zhang, Wei .
IEEE ROBOTICS AND AUTOMATION LETTERS, 2021, 6 (02) :747-754
[5]   Intelligent decoupled controller for mobile inverted pendulum real-time implementation [J].
Chiu, Chih-Hui ;
Peng, Ya-Fu ;
Sun, Chung-Hsun .
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2017, 32 (06) :3809-3820
[6]   Design of a single-input fuzzy logic controller and its properties [J].
Choi, BJ ;
Kwak, SW ;
Kim, BK .
FUZZY SETS AND SYSTEMS, 1999, 106 (03) :299-308
[7]   Learning-Based Balance Control of Wheel-Legged Robots [J].
Cui, Leilei ;
Wang, Shuai ;
Zhang, Jingfan ;
Zhang, Dongsheng ;
Lai, Jie ;
Zheng, Yu ;
Zhang, Zhengyou ;
Jiang, Zhong-Ping .
IEEE ROBOTICS AND AUTOMATION LETTERS, 2021, 6 (04) :7667-7674
[8]   Trajectory Optimization for Wheeled-Legged Quadrupedal Robots Using Linearized ZMP Constraints [J].
de Viragh, Yvain ;
Bjelonic, Marko ;
Bellicoso, C. Dario ;
Jenelten, Fabian ;
Hutter, Marco .
IEEE ROBOTICS AND AUTOMATION LETTERS, 2019, 4 (02) :1633-1640
[9]  
Dong JY, 2022, CHIN CONTR CONF, P450, DOI 10.23919/CCC55666.2022.9902200
[10]  
Hao YJ, 2022, 2ND INTERNATIONAL WORKSHOP ON CYBER-PHYSICAL-HUMAN SYSTEM DESIGN AND IMPLEMENTATION (CPHS 2022), P1, DOI [10.1109/CPHS56133.2022.00005, 10.1109/ACIRS55390.2022.9845589, 10.1109/CPHS56133.2022.9804560]