Search-based Motion Planning Approaches for Two-link Arms

Over the past decade, motion planning in robotics has become not only a popular research field in academia, but also one of the most applicable technologies in various industries. There are two famously known approaches to tackling this problem, namely, the search-based approach and the sampled-based approach, both involving the idea of reposing a motion planning problem as a search problem in the Configuration Space. The main focus of this report is to illustrate how a search-based approach, originally proposed to solve a search problem, can be accommodated for the use of planning the motion of a simulated two-link arm. Moreover, the performance analysis of three different search algorithms, Depth First Search (DFS), Breadth First Search (BFS), and A-Star (A*) for a grid search will be provided to show the conclusion that A* is the best search-based algorithm out of the three to use in practice because it generates the most efficient arm movement with a slight tradeoff in a runtime.