An Approach for Dynamic Obstacle Avoidance in Autonomous Mobile Robots Operating in Unstructured Indoor Environments
Received: 17 March 2025 | Revised: 14 April 2025 | Accepted: 19 April 2025 | Online: 4 June 2025
Corresponding author: Van-Long Trinh
Abstract
This paper deals with mobile robot navigation and obstacle avoidance, presenting a probabilistic search algorithm, Rapidly exploring Random Tree (RRT) method, to ensure stability and flexibility of robots in the face of unexpected events. To optimize the map updating process, the improved RRT automatically builds the map by combining global and local paths. The path is optimized using the Dijkstra algorithm to increase the real-time performance. As the robot moves, the map is continuously updated to detect dynamic obstacles. When an obstacle is detected, a new optimal path is generated to guide the robot to the goal. Experiments on the robot operating system have shown that the optimization works and the robot can automatically avoid static and dynamic obstacles in the simulated environment, map quickly, and avoid small spaces. The results of the study can be extended to movements in unstructured environments and can be used at boundary nodes.
Keywords:
mobile robot, dynamic obstacles, unstructured indoor environments, RRT algorithmDownloads
References
J. Liao, Z. Chen, and B. Yao, "Model-Based Coordinated Control of Four-Wheel Independently Driven Skid Steer Mobile Robot with Wheel–Ground Interaction and Wheel Dynamics," IEEE Transactions on Industrial Informatics, vol. 15, no. 3, pp. 1742–1752, Mar. 2019.
Y. Saidi, A. Nemra, and M. Tadjine, "Robust mobile robot navigation using fuzzy type 2 with wheel slip dynamic modeling and parameters uncertainties," International Journal of Modelling and Simulation, vol. 40, no. 6, pp. 397–420, Nov. 2020.
W. Xue, P. Liu, R. Miao, Z. Gong, F. Wen, and R. Ying, "Navigation system with SLAM-based trajectory topological map and reinforcement learning-based local planner," Advanced Robotics, vol. 35, no. 15, pp. 939–960, Aug. 2021.
Z. He, H. Sun, J. Hou, Y. Ha, and S. Schwertfeger, "Hierarchical Topometric Representation of 3D Robotic Maps," Autonomous Robots, vol. 45, no. 5, pp. 755–771, Jun. 2021.
J. Fu, F. Tian, T. Chai, Y. Jing, Z. Li, and C.-Y. Su, "Motion Tracking Control Design for a Class of Nonholonomic Mobile Robot Systems," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 50, no. 6, pp. 2150–2156, Jun. 2020.
D. Wang, Y. Hu, and T. Ma, "Mobile robot navigation with the combination of supervised learning in cerebellum and reward-based learning in basal ganglia," Cognitive Systems Research, vol. 59, pp. 1–14, Jan. 2020.
T. Du, Y. H. Zeng, J. Yang, C. Z. Tian, and P. F. Bai, "Multi-sensor fusion SLAM approach for the mobile robot with a bio-inspired polarised skylight sensor," IET Radar, Sonar & Navigation, vol. 14, no. 12, pp. 1950–1957, 2020.
P.-C. Song, J.-S. Pan, and S.-C. Chu, "A parallel compact cuckoo search algorithm for three-dimensional path planning," Applied Soft Computing, vol. 94, Sep. 2020, Art. no. 106443.
C. Ren, X. Li, X. Yang, and S. Ma, "Extended State Observer-Based Sliding Mode Control of an Omnidirectional Mobile Robot With Friction Compensation," IEEE Transactions on Industrial Electronics, vol. 66, no. 12, pp. 9480–9489, Dec. 2019.
B. Kasmi and A. Hassam, "Comparative Study between Fuzzy Logic and Interval Type-2 Fuzzy Logic Controllers for the Trajectory Planning of a Mobile Robot," Engineering, Technology & Applied Science Research, vol. 11, no. 2, pp. 7011–7017, Apr. 2021.
H. Medjoubi, A. Yassine, and H. Abdelouahab, "Design and Study of an Adaptive Fuzzy Logic-Based Controller for Wheeled Mobile Robots Implemented in the Leader-Follower Formation Approach," Engineering, Technology & Applied Science Research, vol. 11, no. 2, pp. 6935–6942, Apr. 2021.
R. Seif and M. A. Oskoei, "Mobile Robot Path Planning by RRT* in Dynamic Environments," International Journal of Intelligent Systems and Applications, vol. 7, no. 5, p. 24, Apr. 2015.
A. Tahirovic and G. Magnani, "A Roughness-based RRT for Mobile Robot Navigation Planning," IFAC Proceedings Volumes, vol. 44, no. 1, pp. 5944–5949, Jan. 2011.
H. Ryu and Y. Park, "Improved Informed RRT* Using Gridmap Skeletonization for Mobile Robot Path Planning," International Journal of Precision Engineering and Manufacturing, vol. 20, no. 11, pp. 2033–2039, Nov. 2019.
D. Lin, B. Shen, Y. Liu, F. E. Alsaadi, and A. Alsaedi, "Genetic algorithm-based compliant robot path planning: an improved Bi-RRT-based initialization method," Assembly Automation, vol. 37, no. 3, pp. 261–270, Aug. 2017.
H. Zhang, Y. Wang, J. Zheng, and J. Yu, "Path Planning of Industrial Robot Based on Improved RRT Algorithm in Complex Environments," IEEE Access, vol. 6, pp. 53296–53306, 2018.
Y. Gan, B. Zhang, C. Ke, X. Zhu, W. He, and T. Ihara, "Research on Robot Motion Planning Based on RRT Algorithm with Nonholonomic Constraints," Neural Processing Letters, vol. 53, no. 4, pp. 3011–3029, Aug. 2021.
K. Wei and B. Ren, "A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm," Sensors, vol. 18, no. 2, Feb. 2018, Art. no. 571.
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Copyright (c) 2025 Ngoc-Tien Tran, Thanh-Lam Bui, Van-Long Trinh
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