Navigation planning for a multi robot system exploring an unknown environment supported by volumetric data

Abstract

Exploration and navigation in unknown environments can be done individually or as a group of robots. The current state-of-the-art systems mainly use frontier detection-based exploration approaches based on occupancy grids and are available as either single robot systems or multi-robot systems. In this research, we propose a two-stage octomap-based exploration system for multi-robot systems that improve multi-robot coordinated exploration. We also present a prototype robotic system capable of exploring an unmapped area individually or while coordinating with other robots to complete the exploration fast and efficiently. During single robot exploration, the proposed system only uses the first stage of the two-stage system to evaluate the octomap of the environment. This stage utilizes the state of voxels to calculate target locations for navigation using a distance-based cost function. During multi-robot exploration, the proposed system uses both stages of the two-stage system to explore the given area. The second stage uses maps created by individual robots to create a merged map. The merged map can be used to evaluate the environment using octomaps to identify target locations for exploration and navigation. We have also proposed a performance evaluation criterion for exploration systems considering the robot’s operation time, power consumption, and stability. This criterion was used to evaluate the system and compare the performance of the individual robot system against the multi-robot system as well as against the state-of-the-art Explore-Lite system. Results of experiments show that the individual robot system proposed in this paper is about 38% faster than the Explore-Lite system, the multi-robot system using two robots is 48% faster than the individual robot system, and the multi-robot system using three robots is 38% faster than the individual robot system.