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Path Planning for Robotic Systems in Dynamic Environments: Using RRT*, RRT-D* Lite, and Bi-RRT*-D* Lite | ||
| IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING | ||
| Volume 26, Issue 1, April 2026 PDF (9.62 M) | ||
| Document Type: Research Paper | ||
| DOI: https://doi.org/10.33103/2617-3352.1521 | ||
| Authors | ||
| Hameed Salman Hameed* 1; Omar Farouq Lutfy2; Firas A. Raheem3 | ||
| 1University of technology/ control and systems engineering | ||
| 2College of Control and Systems Engineering, University of Technology-Iraq, Baghdad, Iraq, | ||
| 3Control and System Department, university of Technology | ||
| Abstract | ||
| Path planning is one of the essential challenges in the area of robotic systems. In recent years, Rapidly-exploring Random Tree star (RRT*) has been a preferred path planner for robots due to its probabilistic completeness. This paper explores using three path planning algorithms for a mass point robotic system navigating dynamic environments with RRT*, Bidirectional Rapidly- exploring Random Tree (Bi-RRT*), and a novel hybrid approach (Bi-RRT*-D Lite*). The study shows the performance of these algorithms in terms of the path length, the path generating time, the number of search attempts, and the percentage error. In addition, it compares the Bi-RRT* and the hybrid approach of Bi-RRT*-D*Lite relative to RRT*. We implement each algorithm in MATLAB and evaluate its effectiveness through simulations involving mazes with static and dynamic obstacles. Our findings demonstrate the advantages of the new hybrid approach in handling dynamic obstacles and showing superior efficiency in complex environments. The results showed that the reduction percentages of iteration, path generating time, and path length for Bi-RRT* relative to RRT are 91%, 86%, and 0.33%, respectively. On the other hand, the hybrid approach gives the percentages of improvements of 97%, 97%, and 6.8% compared to RRT. | ||
| Keywords | ||
| Path planning; Dynamic environment; Hybrid approach; Rapidly-exploring random tree star | ||
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