Performance evaluation of robot motion planning algorithms: VIS-PRM vs. AGRM

The aim of This work is to conduct a performance evaluation between the well-known probabilistic roadmap approach, in particular the visibility-based probabilistic roadmap and our proposed art gallery-based roadmap, which is based on a variant of the well-known art gallery theorem. The evaluation would involve several criteria among which are: the cardinality of the graph, the completeness of the algorithm, and the complexity analysis. Our proposed algorithm is robust and fast as it generally covers the whole workspace based on the art gallery problem with a small number of so-called guards as opposed to generating a large number as it is the case in most other approaches. The simulation results illustrate how our proposed algorithm outperforms the visibility-based probabilistic roadmap in terms of time and storage complexities.