the rough terrain will have some features like holes, mountains, flat surface. in the created terrain, we will set start and goal position, then the robot with its behaviour will autonomously navigate to find the goal postion thru the terrain. The performance of each sampling based algorithms will be compared in terms of distance to be travelled, planning time, running costs, feasibility, no of iterations, and success rate
so there will be like 3-5 algorithms
rough terrain features :*
holes, low/High terrain, flat surface, maze, narrow passage, stairs
=>>> set start and goal position
*proposed sampling-based algorithms (RRT variants* :
I-RRT*
Theta*-RRT
Roughness-based RRT
*Parameters to be compared between algorithms:*
each algorithms will run up 10-50 times to reach optimal path towards goal position
– min/max/average no of iterations
– min/max/average time utilized
– Total cost (roughness)
– Distance travelled
– success rate ( fail/success to reach optimal path)
the instructions will be :
1st to create a rough terrain environment as a workspace for the robot simulation.
2nd the mobile robot with path planning algorithm is used to navigate in the workspace . autonomously search for goal position for start position.
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