An obstacle avoidance trajectory control method for intelligent robot based on K decision tree

被引:1
作者
Wang J. [1 ]
机构
[1] Department of Intelligent Manufacturing and Automotive, Chongqing Vocational College of Transportation, Chongqing
关键词
Intelligent robot; K decision tree; Obstacle avoidance; Trajectory control;
D O I
10.1504/IJMTM.2021.118804
中图分类号
学科分类号
摘要
In order to overcome the problem that the existing trajectory control methods of robot avoiding obstacles do not recognise the position and pose of the target, which have large control error, this paper proposes the research of trajectory control method of intelligent robot avoiding obstacles based on K decision tree. The robot motion model and the ultrasonic sensor observation model are established, and the self positioning coordinates are obtained. K-decision tree algorithm is used to extract the visual features of point cloud, build database, target recognition, etc. to achieve the trajectory control of robot obstacle avoidance. The experimental results show that the control accuracy of the proposed method is strong and it is a reliable obstacle avoidance control method for robot. Copyright © 2021 Inderscience Enterprises Ltd.
引用
收藏
页码:218 / 233
页数:15
相关论文
共 22 条
[1]  
Benjamin M.R., Defilippo M., Robinette P., Novitzky M., Obstacle avoidance using multiobjective optimization and a dynamic obstacle manager, IEEE Journal of Oceanic Engineering, 44, 2, pp. 331-342, (2019)
[2]  
Braginsky B., Guterman H., Obstacle avoidance approaches for autonomous underwater vehicle: simulation and experimental results, IEEE Journal of Oceanic Engineering, 41, 4, pp. 882-892, (2016)
[3]  
Delfin J., Becerra H.M., Arechavaleta G., Visual servo walking control for humanoids with finite-time convergence and smooth robot velocities, International Journal of Control, 89, 7, pp. 1-35, (2016)
[4]  
Guerra M., Efimov D.V., Zheng G., Perruquetti W., Finite-time obstacle avoidance for unicycle-like robot subject to additive input disturbances, Autonomous Robots, 41, 1, pp. 1-12, (2017)
[5]  
Hausler A.J., Saccon A., Aguiar A.P., Hauser J., Pascoal A.M., Energy-optimal motion planning for multiple robotic vehicles with collision avoidance, IEEE Transactions on Control Systems Technology, 24, 3, pp. 867-883, (2016)
[6]  
Jiang M., Yuqiao W., Xu Z., Research on obstacle avoidance control of picking robot based on dsp signal real-time coding technology, Journal of Agricultural Mechanization Research, 38, 7, pp. 234-238, (2016)
[7]  
Kalogeiton V.S., Ioannidis K., Sirakoulis G.C., Kosmatopoulos E.B., Real-time active SLAM and obstacle avoidance for an autonomous robot based on stereo vision, Cybernetics and Systems, 50, 3, pp. 239-260, (2019)
[8]  
Kim H., Kim M.J., Electric field control of bacteria-powered microrobots using a static obstacle avoidance algorithm, IEEE Transactions on Robotics, 32, 1, pp. 125-137, (2016)
[9]  
Lee B.H., Jeon J.D., Oh J.H., Velocity obstacle based local collision avoidance for a holonomic elliptic robot, Autonomous Robots, 41, 6, pp. 1-17, (2016)
[10]  
Li L., Chang Q., Wang Y., Simulation on the target obstacles avoidance path optimization of indoor robot service, Computer Simulation, 35, 1, pp. 301-305, (2018)