Name
Abstract | ||
|---|---|---|
The Rapidly Exploring Random Tree Star (RRT*) is an extension of the Rapidly Exploring Random Tree path finding algorithm. RRT* guarantees an optimal, collision free path solution but is limited by slow convergence rates and inefficient memory utilization. This paper presents APGD-RRT*, a variant of RRT* which utilizes Artificial Potential Fields to improve RRT* performance, providing relatively better convergence rates. Simulation results under different environments between the proposed APGD-RRT* and RRT* algorithms demonstrate this marked improvement under various test environments. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ROBIO.2013.6739744 | Robotics and Biomimetics |
Keywords | Field | DocType |
collision avoidance,convergence,mobile robots,trees (mathematics),APGD-RRT*,RRT* performance improvement,adaptive potential guided directional-RRT,artificial potential fields,autonomous robots,collision free path solution,convergence rates,memory utilization,path planning,rapidly exploring random tree path finding algorithm,rapidly exploring random tree star,Artificial Potential Fields,Directional Sampling and Path Planning,Fast Convergence Rate,Optimal Path,RRT∗ | Convergence (routing),Mathematical optimization,Rapidly exploring random tree,Collision free,Mathematics,Mobile robot,Distributed computing | Conference |
Citations | PageRank | References |
4 | 0.50 | 3 |
Authors | ||
10 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmed Hussain Qureshi | 1 | 54 | 8.83 |
| Saba Mumtaz | 2 | 5 | 1.20 |
| Khawaja Fahad Iqbal | 3 | 7 | 1.65 |
| Badar Ali | 4 | 6 | 0.94 |
| Yasar Ayaz | 5 | 63 | 11.39 |
| Faizan Ahmed | 6 | 11 | 1.72 |
| Saeed Muhammad Mannan | 7 | 19 | 2.26 |
| Osman Hasan | 8 | 401 | 60.79 |
| Whoi-Yul Kim | 9 | 518 | 47.84 |
| Moonsoo Ra | 10 | 11 | 4.09 |