Muhammad, Aisha and Hasma Abdullah, Nor Rul and Ali, Mohammed Abdo Hashem and Shanono, Ibrahim Haruna and Samad, Rosdiyana (2022) Simulation performance comparison of A*, GLS, RRT and PRM path planning algorithms. In: 12th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2022, 21-22 May 2022, Virtual, Online.
Full text not available from this repository.Abstract
Path planning is among the essential qualities of an autonomous robot. The ability to build a collision-free pathway from a pre-defined point to another is known as path planning. There are a variety of approaches offered, all of which vary depending on the search pattern and the map representation method. In this study, four robust path planning algorithms, namely: Probabilistic Roadmaps (PRMs), A-star, the Rapidly Exploring Random Trees (RRTs), and Generalized Laser Simulator (GLS), were simulated and their performance was measured and compared according to the total path distance covered, search time and path smoothness. The result obtained reveals that all the four algorithms could navigate and generate a feasible through the 2D map successfully. The GLS algorithm performs better in all the measured parameters followed by the PRM, RRT, and then the A∗ algorithm. © 2022 IEEE.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | Universiti Malaysia Pahang [Grant no. PGRS200342, RDU 200333] |
| Uncontrolled Keywords: | Robot programming; A; Generalized laser simulator; Laser simulators; Path-planning algorithm; Performance comparison; Probabilistic roadmap; Probabilistics; Rapidly-exploring random trees; Roadmap; Simulation performance; Motion planning |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Faculty of Engineering > Department of Mechanical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 18 Feb 2025 02:35 |
| Last Modified: | 18 Feb 2025 02:35 |
| URI: | http://eprints.um.edu.my/id/eprint/43610 |
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