Autonomous exploration of mobile robot equipped with LiDAR for high-quality reconstruction in large-scale indoor environments

Abstract

High-quality 3D reconstruction is essential for applications such as autonomous driving, Augmented Reality (AR)/Virtual Reality (VR), and smart cities. Traditional methods using handheld sensors often result in incomplete and misaligned models. While autonomous exploration can improve these results, it often sacrifices quality for speed. This paper proposes a novel system for high-quality 3D reconstruction of large-scale indoor environments, leveraging a mobile robot equipped with a solid-state LiDAR mounted on a 2-degree-of-freedom (2-DOF) gimbal. The gimbal provides flexible scanning capabilities to overcome field-of-view (FoV) limitations of solid-state LiDARs. To address high-frequency, real-time quality evaluation during exploration, we introduce a new concept called guard-points, which guides the robot toward areas with insufficient point cloud density. These guard-points, alongside conventional frontier-based viewpoints, enable our planner to dynamically balance exploration and reconstruction quality. This system not only controls the mobile robot to visit unknown places and areas with insufficient reconstruction quality but also facilitates high-frequency, real-time exploration path planning. This paper concludes with various simulations and real-world experiments to validate the effectiveness of our system.