A Comparative Study of Deterministic and Probabilistic Mobile Robot Path Planning Algorithms

Abstract

This paper presents a comparative study between seven deterministic and probabilistic mobile robot path planning algorithms. For this purpose, 19 different environments with various complexities were designed and the performance of the (1) A*, (2) Dijkstra, (3) Visibility Graph, (4) Probabilistic Roadmap, (5) Lazy Probabilistic Roadmap, (6) Rapid-exploring Random Tree, and (7) Bidirectional Rapid-exploring Random Tree were assessed in terms of (i) path length, (ii) path smoothness, (iii) runtime, and (iv) success rate for each environment. In addition, for probabilistic algorithms, the parameters of the planners were evaluated to assess their efficiency under different working conditions. This comparison study reveals the advantages and flaws of the mentioned path planning algorithms and provides an informative insight for researchers to select the best path planning method based on their application.