基于速度調節與路徑跟蹤的差動機器人運動控制

張俊娜; 白國星

doi:10.13374/j.issn2095-9389.2022.08.14.003

基于速度調節與路徑跟蹤的差動機器人運動控制

doi: 10.13374/j.issn2095-9389.2022.08.14.003

張俊娜^1,,
白國星^2, ,

1.
山西機電職業技術學院，長治 046011
2.
北京科技大學機械工程學院，北京 100083

基金項目: 國家重點研發計劃資助項目（2018YFE0192900）；中國博士后科學基金資助項目（2022M710354）；中央高校基本科研業務費專項資金資助項目（FRF-TP-20-052A1）

詳細信息

通訊作者:
E-mail: gxbai@ustb.edu.cn

中圖分類號: TP242
計量
- 文章訪問數: 343
- HTML全文瀏覽量: 164
- PDF下載量: 113
- 被引次數: 0
出版歷程
- 收稿日期: 2022-08-14
- 網絡出版日期: 2023-01-12
- 刊出日期: 2023-09-25

Motion control of differential robot based on speed adjusting and path tracking

ZHANG Junna^1
,,
BAI Guoxing^{2
, ,}

1.
Shanxi Institute of Mechanical and Electrical Engineering, Changzhi 046011, China
2.
School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China

More Information

Corresponding author: E-mail: gxbai@ustb.edu.cn

摘要

摘要: 差動機器人是一種常見的移動機器人，在倉儲、農業等行業的應用十分廣泛。針對縱向速度接近最大值時差動機器人跟蹤參考路徑的能力與保持縱向速度的能力之間存在沖突的問題，從差動機器人縱向速度與轉彎曲率之間的映射關系出發，提出了基于預瞄信息的速度調節控制器，并提出了配套的基于非線性模型預測控制的路徑跟蹤控制器，形成了基于速度調節與路徑跟蹤的差動機器人運動控制系統。仿真與實驗結果表明，提出的運動控制系統可以在差動機器人的縱向速度設定值較高時主動調節縱向速度，保障較高的路徑跟蹤控制精確性，其中位移誤差的絕對值不超過0.0499 m，航向誤差的絕對值不超過0.0726 rad，相比無速度調節的運動控制系統，該系統可將位移誤差和航向誤差的最大絕對值分別減少達97.57%和45.04%。
- 差動機器人 /
- 無人駕駛 /
- 運動控制 /
- 速度調節 /
- 路徑跟蹤
Abstract: A differential robot is a typical mobile robot widely used in storage, agriculture, and other industries. The motion control of differential robots, including longitudinal and lateral control, is a current research hotspot. To date, researchers have not paid much attention to the interaction between longitudinal and lateral control of differential robots. However, the conflict between the ability to track the reference path and maintain the longitudinal speed at its maximum value is a critical issue that limits the operational efficiency of the differential robot. To solve this problem, a mapping relationship between the longitudinal speed and the turning curvature is analyzed. The mapping relationship is established when the maximum value of the longitudinal speed is known, i.e., the feasible upper limit of the longitudinal speed that can guarantee the steering ability of the differential robot is inversely proportional to the curvature of the trajectory. From this mapping relationship, a speed-adjusting method is proposed based on the preview information. This speed-adjusting method consists of two steps. First, the smaller value between the upper limit of the feasible longitudinal speed in a certain preview distance and the set value of the longitudinal speed are taken as the desired longitudinal speed. Second, a control law is established based on the deviation between this desired and current longitudinal speed. Additionally, a path-tracking method that cooperates with the above-mentioned speed-adjusting method is proposed. The theoretical basis of this path-tracking method is a nonlinear model predictive control. The prediction model used in this control method is derived from a kinematic model with longitudinal speed as a time-dependent parameter. Finally, a differential robot motion control system is formed based on speed adjusting and path tracking. The simulation and experimental results show that the proposed motion control system can actively adjust the longitudinal speed when the set value of the longitudinal speed of the differential robot is high and ensure high accuracy of path tracking control. Furthermore, the absolute value of the displacement and heading errors does not exceed 0.0499 m and 0.0726 rad, which are reduced by 97.57% and 45.04% compared with the motion control system without speed adjusting, respectively.
- differential robot /
- unmanned driving /
- motion control /
- speed adjusting /
- path tracking

HTML全文

圖 1 控制系統框架

Figure 1. Control system framework

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圖 2 仿真參考路徑

Figure 2. Reference path of the simulation

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圖 3 低設定速度仿真縱向速度

Figure 3. Longitudinal speed of the low-setting speed simulation

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圖 4 低設定速度仿真軌跡

Figure 4. Trajectories of the low-setting speed simulation

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圖 5 低設定速度仿真軌跡局部放大

Figure 5. Local zoom-in of the trajectories of the low-setting speed simulation

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圖 6 低設定速度仿真位移誤差

Figure 6. Displacement error of the low-setting speed simulation

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圖 7 低設定速度仿真航向誤差

Figure 7. Heading error of the low-setting speed simulation

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圖 8 高設定速度仿真縱向速度

Figure 8. Longitudinal speed of the high-setting speed simulation

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圖 9 高設定速度仿真軌跡

Figure 9. Trajectories of the high-setting speed simulation

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圖 10 高設定速度仿真軌跡局部放大

Figure 10. Local zoom-in of the trajectories of the high-setting speed simulation

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圖 11 高設定速度仿真位移誤差

Figure 11. Displacement error of the high-setting speed simulation

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圖 12 高設定速度仿真航向誤差

Figure 12. Heading error of the high-setting speed simulation

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圖 13 實驗設備

Figure 13. Photograph of the differential robot used for the experiment

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圖 14 實驗縱向速度

Figure 14. Longitudinal speed of the experiment

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圖 15 實驗軌跡

Figure 15. Trajectories of the experiment

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圖 16 實驗軌跡局部放大

Figure 16. Local zoom-in of the trajectories of the experiment

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圖 17 實驗位移誤差

Figure 17. Displacement error of the experiment

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圖 18 實驗航向誤差

Figure 18. Heading error of the experiment

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參考文獻(30)

[1]	Jin Y C, Liu J Z, Xu Z J, et al. Development status and trend of agricultural robot technology. Int J Agric Biol Eng, 2021, 14(3): 1
[2]	Yi W Q, Zhao C J, Liu Y. Research on autonomous positioning and navigation technology of mobile robots. Chin J Constr Mach, 2020, 18(5): 400 doi: 10.15999/j.cnki.311926.2020.05.005 易文泉, 趙超俊, 劉瑩. 移動機器人自主定位與導航技術研究. 中國工程機械學報, 2020, 18(5):400 doi: 10.15999/j.cnki.311926.2020.05.005
[3]	Zhu J S, Li W, Lin D, et al. Intelligent fire monitor for fire robot based on infrared image feedback control. Fire Technol, 2020, 56(5): 2089 doi: 10.1007/s10694-020-00964-4
[4]	Li H, Wang C Y. Navigation motion control of warehouse handling robot and NURBS trajectory planning. Mach Des &Manuf, 2020(7): 290 doi: 10.3969/j.issn.1001-3997.2020.07.066 李航, 王朝耀. 倉庫搬運機器人導航運動控制與NURBS軌跡規劃. 機械設計與制造, 2020(7):290 doi: 10.3969/j.issn.1001-3997.2020.07.066
[5]	Stefek A, Van Pham T, Krivanek V, et al. Energy comparison of controllers used for a differential drive wheeled mobile robot. IEEE Access, 2020, 8: 170915 doi: 10.1109/ACCESS.2020.3023345
[6]	Xiong L, Yang X, Zhuo G R, et al. Review on motion control of autonomous vehicles. J Mech Eng, 2020, 56(10): 127 doi: 10.3901/JME.2020.10.127 熊璐, 楊興, 卓桂榮, 等. 無人駕駛車輛的運動控制發展現狀綜述. 機械工程學報, 2020, 56(10):127 doi: 10.3901/JME.2020.10.127
[7]	Bai G X, Meng Y, Liu L, et al. Current status of path tracking control of unmanned driving vehicles. Chin J Eng, 2021, 43(4): 475 白國星, 孟宇, 劉立, 等. 無人駕駛車輛路徑跟蹤控制研究現狀. 工程科學學報, 2021, 43(4):475
[8]	Hartono R, Nizar T N. Speed control of a mobile robot using fuzzy logic controller. IOP Conf Ser:Mater Sci Eng, 2019, 662(2): 022063 doi: 10.1088/1757-899X/662/2/022063
[9]	Ayten K K, ?iplak M H, Dumlu A. Implementation a fractional-order adaptive model-based PID-type sliding mode speed control for wheeled mobile robot. Proc Inst Mech Eng Part I J Syst Control Eng, 2019, 233(8): 1067
[10]	Liu M, Rong X W, Li Y B, et al. Speed adaptive control of mobile robot based on terrain clustering analysis. J Jilin Univ (Eng Technol Ed), 2021, 51(4): 1496 doi: 10.13229/j.cnki.jdxbgxb20200334 劉明, 榮學文, 李貽斌, 等. 基于地形聚類分析的移動機器人速度自適應控制. 吉林大學學報(工學版), 2021, 51(4):1496 doi: 10.13229/j.cnki.jdxbgxb20200334
[11]	Orita Y, Fukao T. Robust human tracking of a crawler robot. J Robot Mechatron, 2019, 31(2): 194 doi: 10.20965/jrm.2019.p0194
[12]	Li Y C, Qiao Y. Design and simulation of path tracking controller for four-wheel robot. Electron Meas Technol, 2019, 42(13): 11 doi: 10.19651/j.cnki.emt.1802550 李一春, 喬毅. 四輪機器人路徑跟蹤控制器設計與仿真. 電子測量技術, 2019, 42(13):11 doi: 10.19651/j.cnki.emt.1802550
[13]	Zhao Z Y, Liu H O, Chen H Y, et al. Kinematics-aware model predictive control for autonomous high-speed tracked vehicles under the off-road conditions. Mech Syst Signal Process, 2019, 123: 333 doi: 10.1016/j.ymssp.2019.01.005
[14]	Yang H J, Wang S Z, Zuo Z Q, et al. Trajectory tracking for a wheeled mobile robot with an omnidirectional wheel on uneven ground. IET Control Theory Appl, 2020, 14(7): 921 doi: 10.1049/iet-cta.2019.1074
[15]	Bai G X, Liu L, Meng Y, et al. Real-time path tracking of mobile robot based on nonlinear model predictive control. Trans Chin Soc Agric Mach, 2020, 51(9): 47 doi: 10.6041/j.issn.1000-1298.2020.09.006 白國星, 劉麗, 孟宇, 等. 基于非線性模型預測控制的移動機器人實時路徑跟蹤. 農業機械學報, 2020, 51(9):47 doi: 10.6041/j.issn.1000-1298.2020.09.006
[16]	Ibraheem G A R, Azar A T, Ibraheem I K, et al. A novel design of a neural network-based fractional PID controller for mobile robots using hybridized fruit fly and particle swarm optimization. Complexity, 2020, 2020: 3067024
[17]	Khalaji A K, Jalalnezhad M. Robust forward\backward control of wheeled mobile robots. ISA Trans, 2021, 115: 32 doi: 10.1016/j.isatra.2021.01.016
[18]	Zhao L, Jin J, Gong J Q. Robust zeroing neural network for fixed-time kinematic control of wheeled mobile robot in noise-polluted environment. Math Comput Simul, 2021, 185: 289 doi: 10.1016/j.matcom.2020.12.030
[19]	Gao X S, Gao R, Liang P, et al. A hybrid tracking control strategy for nonholonomic wheeled mobile robot incorporating deep reinforcement learning approach. IEEE Access, 2021, 9: 15592 doi: 10.1109/ACCESS.2021.3053396
[20]	Liu Z J, Wang X L, Ren Z G, et al. Crawler tractor navigation path tracking control algorithm based on virtual radar model. Trans Chin Soc Agric Mach, 2021, 52(6): 376 doi: 10.6041/j.issn.1000-1298.2021.06.040 劉志杰, 王小樂, 任志剛, 等. 基于虛擬雷達模型的履帶拖拉機導航路徑跟蹤控制算法. 農業機械學報, 2021, 52(6):376 doi: 10.6041/j.issn.1000-1298.2021.06.040
[21]	Gu Q, Bai G X, Meng Y, et al. Efficient path tracking control for autonomous driving of tracked emergency rescue robot under 6G network. Wirel Commun Mob Comput, 2021, 2021: 5593033
[22]	Kang Y T, Zhang Y, Zeng R Y. Path tracking control of tracked vehicles considering skid-steer characteristics on uneven terrain. J Central South Univ (Sci Technol), 2022, 53(2): 491 康翌婷, 張煜, 曾日芽. 地面不平條件下考慮滑動轉向特性的履帶車輛路徑跟蹤控制. 中南大學學報(自然科學版), 2022, 53(2):491
[23]	Wu H M, Zaman M Q. LiDAR based trajectory-tracking of an autonomous differential drive mobile robot using fuzzy sliding mode controller. IEEE Access, 2022, 10: 33713 doi: 10.1109/ACCESS.2022.3162244
[24]	Sidek N, Sarkar N. Dynamic modeling and control of nonholonomic mobile robot with lateral slip // Third International Conference on Systems. Cancun, 2008: 66
[25]	Bai G X, Liu L, Meng Y, et al. Path tracking of wheeled mobile robots based on dynamic prediction model. IEEE Access, 2019, 7: 39690 doi: 10.1109/ACCESS.2019.2903934
[26]	Bai G X, Meng Y, Liu L, et al. Anti-sideslip path tracking of wheeled mobile robots based on fuzzy model predictive control. Electron Lett, 2020, 56(10): 490 doi: 10.1049/el.2019.4019
[27]	Gu Q, Bai G X, Meng Y, et al. Path tracking of automatic parking based on nonlinear model predictive control. Chin J Eng, 2019, 41(7): 947 顧青, 白國星, 孟宇, 等. 基于非線性模型預測控制的自動泊車路徑跟蹤. 工程科學學報, 2019, 41(7):947
[28]	Bai G X, Meng Y, Liu L, et al. Review and comparison of path tracking based on model predictive control. Electronics, 2019, 8(10): 1077 doi: 10.3390/electronics8101077
[29]	Bai G X, Zhou L, Meng Y, et al. Path tracking of unmanned vehicles based on the time-varying local model. Chin J Eng, 2023, 45(5): 787 白國星, 周蕾, 孟宇, 等. 基于時變局部模型的無人駕駛車輛路徑跟蹤. 工程科學學報, 2023, 45(5):787
[30]	Bai G X, Meng Y, Gu Q, et al. Some rules for setting the horizon parameters of NMPC-based vehicle path tracking // 2020 Chinese Automation Congress (CAC). Shanghai, 2021: 5167