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Adaptive Potential guided directional-RRT
- Authors
- Qureshi, Ahmed Hussain; Mumtaz, Saba; Iqbal, Khawaja Fahad; Ali, Badar; Ayaz, Yasar; Ahmed, Faizan; Muhammad, Mannan Saeed; Hasan, Osman; Kim, Whoi Yul; Ra, Moonsoo
- Issue Date
- Dec-2013
- Publisher
- IEEE Computer Society
- Keywords
- Artificial Potential Fields; Directional Sampling and Path Planning; Fast Convergence Rate; Optimal Path; RRT
- Citation
- 2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013, pp 1887 - 1892
- Pages
- 6
- Indexed
- SCOPUS
- Journal Title
- 2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013
- Start Page
- 1887
- End Page
- 1892
- ISSN
- 0000-0000
- 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.
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