System of Autonomous Aerial Vehicles for Subterranean Exploration with Slam Capabilities

Abstract

Autonomously operating unmanned aerial vehicles (UAVs) are vital for exploring unknown spaces. Search and rescue missions, building mapping, surveying, reconnaissance, and extraterrestrial cave and lava tube exploration all benefit from a robust system of vehicles capable of remote exploration. This work realizes a system of drones for the exploration of such spaces. The presented system consists of lightweight quadcopters that employ Visual-Inertial SLAM for real-time localization and Time of Flight occupancy grid mapping for real-time 3D mapping, yielding similar results to the online SLAM solution but without the need for a 360-degree 3D LiDAR scanner. A custom 3D printed mounting system is utilized to carry a headlamp for illuminating dark environments during viSLAM flight. A waypoint-based Leader-Follower algorithm and a custom MAVLink-based ground station are deployed to control the system and direct the swarm of UAVs in a train configuration. A DCNN is integrated into the UAV system to facilitate real-time object detection and empower autonomous navigation. Complete system flight tests in an artificial cave environment are conducted to evaluate system communication, navigation, and 3D mapping ability. Robust leader-follower configuration, 3D occupancy mapping at resolutions of 0.05 meters, accurate localization in GPS-denied and low-light conditions, and autonomous mission capabilities are all demonstrated.