Topology optimization techniques for mobile robot path planning

This paper proposes an explicit growth-based topology optimizer to generate optimal paths for a point robot moving in complex environments filled with obstacles. The idea is inspired by the intuitive analogy between a robot moving path and a heat transferring path. The feasible regions where a robot can pass through are defined as the design domain on which conduction heat transfer occurs, obstacles are modeled as thermal insulators, and the start and goal points are regarded as a heat source and heat sink. Based on this, the path planning problem is formulated as a topology optimization problem, in which the identification of heat transferring path is implemented by an adaptive growth procedure of high conductivity material link that minimizes thermal compliance. To make heat transferring paths (i.e., cooling channels) being able to grow freely within the design domain, a new method called the conductivity spreading approach (CSA) is developed to eliminate the growth dependency on the underlying ground structure. The suggested method is shown to be effective in all tested benchmark problems including path planning going through a stopover and problems involving more complex terrain conditions. This work suggests new potential applications of heat conduction topology optimization to non-traditional fields and is practically attractive to various path planning problems.