Local path planning for autonomous mobile robots by integrating modified dynamic-window approach and improved follow the gap method

被引:29
作者
Hossain, Tagor [1 ]
Habibullah, Habibullah [1 ]
Islam, Rafiqul [1 ]
Padilla, Ricardo, V [2 ]
机构
[1] Univ South Australia, Fac UniSA STEM, Mawson Lakes, SA 5095, Australia
[2] Southern Cross Univ, SESE, Lismore, NSW, Australia
关键词
autonomous mobile robot; collision avoidance; dynamic obstacles; IFGM-DWA algorithm; local path planning; TIME OBSTACLE AVOIDANCE; VECTOR FIELD HISTOGRAM; NAVIGATION; ALGORITHM; ENVIRONMENT; STRATEGIES; CAR;
D O I
10.1002/rob.22055
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Mobile robots need to automatically generate a safe, goal-oriented, and fast collision-free trajectory in real-time during the movement in an indoor/outdoor environment. A planned trajectory must be adaptable and drivable with environmental changes where various static and moving obstacles may be present. The ultimate goal of a robot is to reach the destination without hitting any obstacles, therefore, a reactive local path planning algorithm is needed. In this paper, a novel local algorithm is proposed by integrating dynamic window approach (DWA) and improved follow the gap method (IFGM) to generate a collision-free trajectory for a mobile robot which is capable to avoid any moving obstacles presenting in the surrounding environment. In this proposed method, first, a safety distance is maintained according to the relative position of obstacles and the robot. Moreover, find a feasible gap to direct the robot toward the desired goal. Besides, the heading angle is calculated to change the direction of the robot for avoiding collision with nearby obstacles. After that, calculate the appropriate velocity for the robot. Finally, a robust, safe, and goal-directed trajectory is generated which does not suffer from global convergence and local minima problems. The performance and effectiveness of this proposed algorithm are evaluated by experimental results.
引用
收藏
页码:371 / 386
页数:16
相关论文
共 48 条
[31]   Path planning of mobile robot by mixing experience with modified artificial potential field method [J].
Min, Huasong ;
Lin, Yunhan ;
Wang, Sijing ;
Wu, Fan ;
Shen, Xia .
ADVANCES IN MECHANICAL ENGINEERING, 2015, 7 (12)
[32]  
Minguez J., 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, P2284
[33]  
Minguez J, 2000, 2000 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2000), VOLS 1-3, PROCEEDINGS, P2094, DOI 10.1109/IROS.2000.895280
[34]   A convergent dynamic window approach to obstacle avoidance [J].
Ögren, P ;
Leonard, NE .
IEEE TRANSACTIONS ON ROBOTICS, 2005, 21 (02) :188-195
[35]   A Hybrid Obstacle Avoidance Method: Follow the gap with dynamic window approach [J].
Ozdemir, Aykut ;
Sezer, Volkan .
2017 FIRST IEEE INTERNATIONAL CONFERENCE ON ROBOTIC COMPUTING (IRC), 2017, :257-262
[36]   V-REP-based navigation of automated wheeled robot between obstacles using PSO-tuned feedforward neural network [J].
Pandey, Anish ;
Panwar, Vikas Singh ;
Hasan, Md Ehtesham ;
Parhi, Dayal R. .
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING, 2020, 7 (04) :427-434
[37]   Autonomous mobile robot navigation between static and dynamic obstacles using multiple ANFIS architecture [J].
Pandey, Anish ;
Kashyap, Abhishek Kumar ;
Parhi, Dayal R. ;
Patle, B. K. .
WORLD JOURNAL OF ENGINEERING, 2019, 16 (02) :275-286
[38]   Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm [J].
Pandey, Anish ;
Parhi, Dayal R. .
DEFENCE TECHNOLOGY, 2017, 13 (01) :47-58
[39]   A review: On path planning strategies for navigation of mobile robot [J].
Patle, B. K. ;
Babu, Ganesh L. ;
Pandey, Anish ;
Parhi, D. R. K. ;
Jagadeesh, A. .
DEFENCE TECHNOLOGY, 2019, 15 (04) :582-606
[40]   OPTIMAL PATHS FOR A CAR THAT GOES BOTH FORWARDS AND BACKWARDS [J].
REEDS, JA ;
SHEPP, LA .
PACIFIC JOURNAL OF MATHEMATICS, 1990, 145 (02) :367-393