Multi-Point Path Planning Algorithm for a Mobile Robot With Composite Moving Costs

Abstract

Multi-point path planning problem is a classic problem of the mobile robot. The present research is concerned with solving the shortest path. In some realistic applications, the shortest path length is not always the significant concerned value of path planning. This article proposes an extended generalized cost concept to constitute the updated path planning strategy. The generalized costs are the combination of straightly moving and turning costs. A genetic algorithm is used to solve optimal path-planning problems. The different weight between the two kinds of costs and how the different parameters affect the optimal path solution is discussed. The generalized cost concept extends the application of path planning to diversified physical quantities. When estimating the composite optimal costs of the path planning problem, we only need to solve the path planning problem with simplex straightly moving costs or simplex turning costs.