A Modified Dijkstra Algorithm for ROS Based Autonomous Mobile Robots

Autonomous Mobile Robots (AMRs) are frequently used in many fields of technology. In this study, an AMR was designed to execute different path planning algorithms. Firstly, working principle, system architecture and motion planning of AMR are presented. Then, a map for the current environment is produced by a Robot Operating System (ROS) powered AMR which was designed for this study. The AMR locates itself on the produced map with the aid of an integrated Light Detection and Ranging sensor (LIDAR). The locomotion of AMR to a user-defined target on the produced map is performed by an optimal path based on AMR's own navigation plan. Two different path planning algorithms, which are Dijkstra’s algorithm and a modified version of Dijkstra’s algorithm, are executed on a cost-effective AMR platform, which has the capability of Simultaneous Localization and Mapping (SLAM). The reason why Dijkstra algorithm is handled in this study rather than A*, D* and RRT algorithms is that this algorithm is a basic and widely used algorithm. Dijkstra’s algorithm is modified, and pros and cons of the modified algorithm are analysed compared to Dijkstra algorithm. The proposed algorithm and navigation of AMR are tested both in real time in real world and as a simulation in Gazebo. Two algorithms were compared according to the results obtained from the robot locomotion both in real application and simulation environment. It is observed that the modified version of the Dijkstra’s algorithm comparatively yielded a bit more satisfactory results in the aspect of path planning.

Keywords:

AMR, dijkstra algorithm, path planning Robot Navigation, ROS,

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Arkin, R. C., & Murphy, R. R. (1990). Autonomous navigation in a manufacturing environment. IEEE Transactions on Robotics and Automation, 6(4), 445–454. https://doi.org/10.1109/70.59355
Ben-Ari Mordechaiand Mondada, F. (2018). Robots and Their Applications . In Elements of Robotics (pp. 1–20). Springer International Publishing. https://doi.org/10.1007/978-3-319-62533-1_1
Carlucho, I., De Paula, M., & Acosta, G. G. (2019). Double Q-PID algorithm for mobile robot control. Expert Systems with Applications, 137, 292–307. https://doi.org/https://doi.org/10.1016/j.eswa.2019.06.066
Durrant-Whyte, H., & Bailey, T. (2006). Simultaneous localization and mapping: part I. IEEE Robotics Automation Magazine, 13(2), 99–110. https://doi.org/10.1109/MRA.2006.1638022
Fadzli, S. A., Abdulkadir, S. I., Makhtar, M., & Jamal, A. A. (2015). Robotic Indoor Path Planning Using Dijkstra’s Algorithm with Multi-Layer Dictionaries. 2015 2nd International Conference on Information Science and Security (ICISS), 1–4. https://doi.org/10.1109/ICISSEC.2015.7371031
Guo, C. (2013). A Solution to Best Itinerary Problem Based on Strategy Set under Dijkstra Algorithm. Applied Mechanics and Materials, 333–335, 1442–1445. https://doi.org/10.4028/www.scientific.net/AMM.333-335.1442
Hartomo, K., Ismanto, B., Nugraha, A., Yulianto, S., & Laksono, B. (2019). Searching the shortest route to distribute disaster’s logistical assistance using Dijkstra method. Journal of Physics: Conference Series, 1402(7), 77014. https://doi.org/10.1088/1742-6596/1402/7/077014
http://wiki.ros.org/tf. (2021, November 2).
https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm. (13 C.E., December 21).
Köseoğlu, M., Çelik, O. M., & Pektaş, Ö. (2017). Design of an autonomous mobile robot based on ROS. 2017 International Artificial Intelligence and Data Processing Symposium (IDAP), 1–5. https://doi.org/10.1109/IDAP.2017.8090199
Kumar, A., & Gao, N. (2021). OPTIMIZATION OF DISTRIBUTION ROUTE USING DIJKSTRA’S BASED GREEDY ALGORITHM : CASE OF RETAIL CHAIN. 6(8), 186–190.
Ochiai, Y., Takemura, K., Ikeda, A., Takamatsu, J., & Ogasawara, T. (2014). Remote control system for multiple mobile robots using touch panel interface and autonomous mobility. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 3272–3277. https://doi.org/10.1109/IROS.2014.6943017
Panigrahi, P. K., & Bisoy, S. K. (2021). Localization strategies for autonomous mobile robots: A review. Journal of King Saud University - Computer and Information Sciences. https://doi.org/https://doi.org/10.1016/j.jksuci.2021.02.015 Roland SIEGWART, Illah R. NOURBAKHSH, & Davide Scaramuzza. (2011). Introduction to Autonomous Mobile Robots (Second Edition, Vol. 5). The MIT Press.
Tsai, C.-C. (1998). A localization system of a mobile robot by fusing dead-reckoning and ultrasonic measurements. IEEE Transactions on Instrumentation and Measurement, 47(5), 1399–1404. https://doi.org/10.1109/19.746618
Wolf, D. F., & Sukhatme, G. S. (2005). Mobile Robot Simultaneous Localization and Mapping in Dynamic Environments. Autonomous Robots, 19(1), 53–65. https://doi.org/10.1007/s10514-005-0606-4
Zaman, S., Slany, W., & Steinbauer, G. (2011). ROS-based mapping, localization and autonomous navigation using a Pioneer 3-DX robot and their relevant issues. 2011 Saudi International Electronics, Communications and Photonics Conference (SIECPC), 1–5. https://doi.org/10.1109/SIECPC.2011.5876943