Abstract
Finding the optimum path for mobile robots is now an essential task as lots of autonomous mobile robots are widely used in factories, hospitals, farms, etc. Many path planning algorithms have been developed to finding the optimum path with the minimum processing time. The vertical cell decomposition algorithm (VCD) is one of the popular path planning algorithms. It is able to find a path in a very short time. In this paper, we present a new algorithm, called the Radial cell decomposition (RCD) algorithm, which can generate shorter paths and a slightly faster than VCD algorithm. Furthermore, the VCD algorithm cannot be applied directly to obstacles in special cases, like two vertices have the same x-coordinate; on the other hand, the RCD algorithm can be applied to these special cases directly. In addition to that, the RCD algorithm is very suitable for corridor environments, unlike the VCD algorithm. In this paper, the RCD algorithm is described and tested for both cluttered and corridor environments. Furthermore, Two different algorithms A*, and Vertical cell decomposition are compared to the RCD algorithm. Simulation results confirm the effectiveness of the RCD algorithm in terms of path length and processing time.
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