MECHANICAL & APPLIED SCIENCE DOMAIN
Published August 2, 2022 | Version v1
Journal article Open

SIMULATION PERFORMANCE COMPARISON OF DIJKSTRA'S ALGORITHM, A *ALGORITHM, AND DYNAMIC WINDOW APPROACH FOR MOBILE ROBOT PATH PLANNING

Authors/Creators

  • 1. Department of Mechanical Engineering, OUTR, Bhubaneswar, Odisha, India

Description

Path planning is one of the significant aspects of mobile robots. Selection of an optimal or sub-optimal collision-free route from initial point to the final point by the mobile robot is known as path planning. In this thesis we have compared the performance of Dijkstra’s Algorithm, A* Algorithm and Dynamic Window Approach. The result was analyzed according to the feasibility and time taken. Results obtained by Dynamic Window Approach found to be feasible in almost all maps whereas the paths obtained by Dijkstra’s algorithm and A* algorithm were not feasible for some of the cases. Time taken for Dijkstra’s algorithm and A* algorithm are less than the time taken for Dynamic Window Approach. But as in some cases the path obtained for Dijkstra’s algorithm and A* algorithm are not feasible, Dynamic Window Approach can be considered as the suitable path planning method.

Files

SIMULATION PERFORMANCE.pdf

Files (885.7 kB)

Name Size Download all
md5:4dc862e405861a8cd3729e9d78ed5186
885.7 kB Preview Download

Additional details

References

  • A. M. Abdulazeez and F. S. Faizi, "Vision-Based Mobile Robot Controllers: A Scientific Review," p. 18, 2021.
  • Md. A. K. Niloy et al., "Critical Design and Control Issues of Indoor Autonomous Mobile Robots: A Review," IEEE Access, vol. 9, pp. 35338–35370, 2021, doi: 10.1109/ACCESS.2021.3062557.
  • V. Kunchev, L. Jain, V. Ivancevic, and A. Finn, "Path Planning and Obstacle Avoidance for Autonomous Mobile Robots: A Review," in Knowledge-Based Intelligent Information and Engineering Systems, vol. 4252, B. Gabrys, R. J. Howlett, and L. C. Jain, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006, pp. 537–544. doi: 10.1007/11893004_70.
  • D. H. Lee, S. S. Lee, C. K. Ahn, P. Shi, and C.-C. Lim, "Finite Distribution Estimation-Based Dynamic Window Approach to Reliable Obstacle Avoidance of Mobile Robot," IEEE Trans. Ind. Electron., vol. 68, no. 10, pp. 9998–10006, Oct. 2021, doi: 10.1109/TIE.2020.3020024.
  • Y. Deng, Y. Chen, Y. Zhang, and S. Mahadevan, "Fuzzy Dijkstra algorithm for shortest path problem under uncertain environment," Appl. Soft Comput., vol. 12, no. 3, pp. 1231–1237, Mar. 2012, doi: 10.1016/j.asoc.2011.11.011.
  • M. Akram, A. Habib, and J. C. R. Alcantud, "An optimization study based on Dijkstra algorithm for a network with trapezoidal picture fuzzy numbers," Neural Comput. Appl., vol. 33, no. 4, pp. 1329–1342, Feb. 2021, doi: 10.1007/s00521-020-05034-y
  • A. Muhammad, M. A. H. Ali, and I. H. Shanono, "Path Planning Methods for Mobile Robots: A systematic and Bibliometric Review," p. 21, 2020.
  • L. Chang, L. Shan, C. Jiang, and Y. Dai, "Reinforcement based mobile robot path planning with improved dynamic window approach in unknown environment," Auton. Robots, vol. 45, no. 1, pp. 51–76, Jan. 2021, doi: 10.1007/s10514-020-09947-4.
  • B. Tang, K. Hirota, J. Wang, Y. Dai, and Z. Jia, "An Improved Dynamic Window Approach for Intelligent Pedestrian Avoidance of Mobile Robot," p. 6, 2020.
  • A. M. Abdulazeez and F. S. Faizi, "Vision-Based Mobile Robot Controllers: A Scientific Review," p. 18, 2021. 2. Md. A. K. Niloy et al., "Critical Design and Control Issues of Indoor Autonomous Mobile Robots: A Review," IEEE Access, vol. 9, pp. 35338–35370, 2021, doi: 10.1109/ACCESS.2021.3062557. 3. V. Kunchev, L. Jain, V. Ivancevic, and A. Finn, "Path Planning and Obstacle Avoidance for Autonomous Mobile Robots: A Review," in Knowledge-Based Intelligent Information and Engineering Systems, vol. 4252, B. Gabrys, R. J. Howlett, and L. C. Jain, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006, pp. 537–544. doi: 10.1007/11893004_70. 4. D. H. Lee, S. S. Lee, C. K. Ahn, P. Shi, and C.-C. Lim, "Finite Distribution Estimation-Based Dynamic Window Approach to Reliable Obstacle Avoidance of Mobile Robot," IEEE Trans. Ind. Electron., vol. 68, no. 10, pp. 9998–10006, Oct. 2021, doi: 10.1109/TIE.2020.3020024. 5. Y. Deng, Y. Chen, Y. Zhang, and S. Mahadevan, "Fuzzy Dijkstra algorithm for shortest path problem under uncertain environment," Appl. Soft Comput., vol. 12, no. 3, pp. 1231–1237, Mar. 2012, doi: 10.1016/j.asoc.2011.11.011. 6. M. Akram, A. Habib, and J. C. R. Alcantud, "An optimization study based on Dijkstra algorithm for a network with trapezoidal picture fuzzy numbers," Neural Comput. Appl., vol. 33, no. 4, pp. 1329–1342, Feb. 2021, doi: 10.1007/s00521-020-05034-y. 7. A. Muhammad, M. A. H. Ali, and I. H. Shanono, "Path Planning Methods for Mobile Robots: A systematic and Bibliometric Review," p. 21, 2020. 8. L. Chang, L. Shan, C. Jiang, and Y. Dai, "Reinforcement based mobile robot path planning with improved dynamic window approach in unknown environment," Auton. Robots, vol. 45, no. 1, pp. 51–76, Jan. 2021, doi: 10.1007/s10514-020-09947-4. 9. B. Tang, K. Hirota, J. Wang, Y. Dai, and Z. Jia, "An Improved Dynamic Window Approach for Intelligent Pedestrian Avoidance of Mobile Robot," p. 6, 2020. 10. H. Q. T. Ngo, V. N. Le, V. D. N. Thien, T. P. Nguyen, and H. Nguyen, "Develop the socially human-aware navigation system using dynamic window approach and optimize cost function for autonomous medical robot," Adv. Mech. Eng., vol. 12, no. 12, p. 1687814020979430, Dec. 2020, doi: 10.1177/1687814020979430