Simulation performance comparison of A*, GLS, RRT and PRM path planning algorithms
Document Type
Conference Item
Publication Date
1-1-2022
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.
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
Divisions
mechanical
Funders
Universiti Malaysia Pahang [Grant no. PGRS200342, RDU 200333]
Publication Title
2022 12th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2022
Publisher
Institute of Electrical and Electronics Engineers Inc.
Event Title
12th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2022
Event Location
Virtual, Online
Event Dates
21-22 May 2022
Event Type
conference