Real-time Map Building and Area Coverage in Unknown Environments

Abstract

Area-covering operation is a special kind of path planning, which requires the robot path to cover every part of the workspace. In this paper, a neural dynamics based algorithm is proposed for real-time map building and area-covering operations. A local map composed of squared cells is built through the proposed neural dynamics during area-covering operations with limited sensory information in unknown environments. The robot is able to dynamically build an accurate map of its immediate limited surroundings for its navigation. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation derived from Hodgkin and Huxley’s membrane equation. The robot can only sense a limited measurable range and the obtained sensory information are used for its navigation. The feasibility of the proposed algorithm is validated by simulation studies on cases under unknown environments.