INTRODUCTION
In this project, I have made use of one of the path planning algorithms namely, Rapidly Growing Random Trees also called as RRTs. An RRT is an algorithm designed to efficiently search non-convex, high-dimensional spaces by randomly building a space-filling tree which is constructed incrementally from samples drawn randomly from search space and are biased to grow towards the large un searched areas of the configuration space. The RRTs can also be considered as a technique to generate open-loop trajectories for non-linear systems with state constraints.
A CHALLENGING PROJECT
Sharing with Others
I have Implemented RRT using python. I have always been intrigued by the subject of this project, and wanted to explore it further. Taking on this task gave me the opportunity to conduct serious research and produce high-quality work. Moreover, while documenting the entire process, I learned a lot about various methodologies and testing techniques. I’m thrilled about the result, and look forward to the next challenge.
PROJECT BODY
Supporting Claims
I have considered a discrete space depicting the shape of a simpler maze. The robot as specified, is a holonomic point robot. Since the environment is a maze, every boundary of the maze is considered an obstacle and whenever an obstacle is reached, the robot traces back its path and updates the path again towards the goal. I have implement collision avoidance myself which ensured that the body is stable and undamaged during the process. This has been implemented in the python environment.
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