An Autonomous Exploration Method Integrating Local Multi-Point TOF Data and Edge Following

Efficient exploration of the environment using a mobile robot within a map is a crucial aspect of Simultaneous Localization and Mappin (SLAM) for robots. However, the autonomous exploration of raster map built by visual SLAM poses a challenge. To address this, this paper proposes a method for autonomous exploration that combines local multi-point TOF (Time-of-Flight) data with edge following. The method first analyzes the local multi-point TOF data in conjunction with a local raster map created by visual SLAM. The search candidate frontier points are obtained and the method for final exploration of the frontier points is determined for implementation. To enhance the precision of autonomous exploration and improve the closed-loop detection rate of visual SLAM, this paper also proposes an exploration strategy that follows the edges in the bypass regions based on the frontier exploration method. The rapidity and effectiveness of our method is verified by comparing it with traditional methods.