Optimal complete coverage planning of wall-climbing robot using improved biologically inspired neural network

Abstract

In order to avoid the ineffectiveness when the biologically inspired neural network is applied to complete coverage path planning, we proposed an improved method for the complete coverage planning of wall-climbing robot with minimum energy consumption. An energy model for wall-climbing robot was built, and then a new next-step selection strategy is proposed from the perspective of optimal global energy consumption. The simulated contrast experiments show that the improved biologically inspired neural network algorithm can perform coverage task efficiently.