Motion planning of differential driven robot based on tracking

被引：0

作者：

Liu Y.-B. ^{[1
]}

Jiang Y.-Y. ^{[2
]}

机构：

[1] School of Mechanics and Optoelectronic Physics, Anhui University of Science and Technology, Huainan

[2] College of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan

来源：

Kongzhi yu Juece/Control and Decision | 2023年 / 38卷 / 09期

关键词：

collision detection; motion planning; tracking way points; triangular mesh; waypoints;

D O I：

10.13195/j.kzyjc.2021.2025

中图分类号：

学科分类号：

摘要：

When using the triangular mesh method in path planning, aiming at the problem that the maximum threshold of the D-P algorithm for extracting waypoints is not easy to determine, this paper proposes a method for extracting waypoints based on collision detection. The Pure Pursuit algorithm is used to track the way points and plan the motion of the differential driven robot. The experimental results show that the collision detection method is better than the D-P algorithm in extracting waypoints. Finally, the motion planning experiment of the differential driven robot shows that the motion trajectory planned by the Pure Pursuit algorithm tracking waypoints is a smooth curve, which can effectively avoid obstacles on the map. The angular velocity and linear velocity of the robot are smooth functions with gentle changes. There are small fluctuations near the waypoints, and the fluctuation range is within the allowable value. The motion planning time is 0.049 s, which can fully meet the actual needs. The results show that the motion planning of mobile robot based on road marking tracking is a simple and effective motion planning method. © 2023 Northeast University. All rights reserved.

引用

页码：2529 / 2536

页数：7

共 27 条

[1] Elbanhawi M, Simic M., Sampling-based robot motion planning: A review, IEEE Access, 2, pp. 56-77, (2014)
[2] Tzafestas S G., Mobile robot control and navigation: A global overview, Journal of Intelligent & Robotic Systems, 91, 1, pp. 35-58, (2018)
[3] Lashkari N, Biglarbegian M, Yang S X., Development of novel motion planning and controls for a series of physically connected robots in dynamic environments, Journal of Intelligent & Robotic Systems, 95, 2, pp. 291-310, (2019)
[4] Ge S, Cui Y., Dynamic motion planning for mobile robots using potential field method, Autonomous Robots, 13, pp. 207-222, (2002)
[5] Maekawa T, Noda T, Tamura S, Et al., Curvature continuous path generation for autonomous vehicle using B-spline curves, Computer-Aided Design, 42, 4, pp. 350-359, (2010)
[6] Bhattacharya P, Gavrilova M L., Roadmap-based path planning-using the voronoi diagram for a clearance-based shortest path, IEEE Robotics & Automation Magazine, 15, 2, pp. 58-66, (2008)
[7] Jan G E, Sun C C, Tsai W C, Et al., An O(n log n) shortest path algorithm based on delaunay triangulation, IEEE/ASME Transactions on Mechatronics, 19, 2, pp. 660-666, (2014)
[8] Elbanhawi M, Simic M, Jazar R., Autonomous robots path planning: An adaptive roadmap approach, Applied Mechanics and Materials, 373, pp. 246-254, (2013)
[9] Cowlagi R V, Tsiotras P., Multiresolution motion planning for autonomous agents via wavelet-based cell decompositions, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42, 5, pp. 1455-1469, (2012)
[10] Pun-Cheng L S C, Tang M Y F, Cheung I K L., Exact cell decomposition on base map features for optimal path finding, International Journal of Geographical Information Science, 21, 2, pp. 175-185, (2007)

← 1 2 3 →