Advancements for A* and RRT in 3D path planning of UAVs

Abstract

Advancements in Unmanned Aerial Vehicles (UAVs) design, actuator and sensory systems and control are making such devices financially available to a wide spectrum of users with various demands and expectations. To mitigate with this ever increasing demand robust, efficient and application–specific path planning is important. This paper presents advancements over the A* and the smoothing algorithms presented in, 1 utilising the same test scenarios. Analysis of results in 1 showed a ripple in path length as the resolution changes for all scenarios considered and less than 0.1% path length improvements after certain amount of smoothing iterates. To attenuate the path length ripple, the A* ripple reduction algorithm was developed. Results show a reduction of more than 46% in terms of standard deviation with respect to the original A* algorithm without any increase in the mean path length for all scenarios. Secondly, the smoothing algorithm developed in 1 was improved to stop smoothing based on the rate of smoothing of previous iterates. Results show more than 10 multiple less path smoothing time maintaining a path length reduction especially for simple scenarios. These advancements further portray the discussed path planning algorithms as candidates to the realisation of online 3D UAV path planning.