Abstract
Path planning is extensively used in different fields not only in robotics but also in games, manufacturing, auto-motive applications, and so on. Robot path planning is one of the major research issues in the area of autonomous mobile robot. The critical step in path planning problem is to find the shortest path from the start position to a defined goal position through a known, unknown, or partially known environment. Hazardous events that may devastate some parts of the intended area convert those areas to untraversable areas. These events introduce topological constraints for the robot motion because of information discrepancy about the environment before and after the damage. In this study, the authors propose a novel method, FreeD∗, to find the shortest path by exploiting the benefits of D∗, Dijkstra, and artificial potential field (APF) algorithms. The generated path using D∗ is optimised using Dijkstra by combining D∗ sub-paths into a single diagonal path if there is no known obstacle between them. Then, APF is used in unknown obstacle avoidance. The simulation results using Webots simulator demonstrate the effectiveness of FreeD∗ in avoiding unknown obstacles with shortest path.
Author supplied keywords
- FreeD∗
- artificial potential field algorithms
- automotive applications
- autonomous mobile robot
- collision avoidance
- defined goal position
- generated path
- hazardous events
- intended area
- mobile robots
- motion control
- partially known environment
- path planning problem
- robot motion
- robot path planning
- short collision free path
- shortest path
- single diagonal path
- start position
- unknown environment
- untraversable areas
Cite
CITATION STYLE
Al-darwbi, M., & Baroudi, U. (2019). FreeD∗: a mechanism for finding a short and collision free path. IET Cyber-Systems and Robotics, 1(2), 55–62. https://doi.org/10.1049/iet-csr.2019.0001
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