SLAM-based Safe Indoor Exploration Strategy

2025-08-19

AI Summary

This paper addresses safe autonomous exploration for circular-profile robots with pose-response latency (e.g., differential-drive self-balancing robots) in unknown cluttered environments. Methodologically, it integrates IMU, 3D LiDAR, and RGB-D data within an RTAB-Map SLAM framework to achieve robust mapping and loop closure detection. A safety-aware skeleton of obstacles is constructed, where skeleton opening directions determine exploration priority, and the robot is constrained to traverse paths with high safety margins. The key contribution lies in tightly coupling geometric safety constraints—ensuring a minimum clearance from obstacles—with topological exploration guidance—driven by skeleton openings—thereby balancing collision robustness and exploration efficiency. Experimental validation in ROS-based indoor scenarios demonstrates stable, collision-free navigation, significantly improving safety-boundary maintenance and coverage rate of unknown regions.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Natural Language Processing: Safety and Robustness
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Large-scale security measurements

Abstract

This paper suggests a 2D exploration strategy for a planar space cluttered with obstacles. Rather than using point robots capable of adjusting their position and altitude instantly, this research is tailored to classical agents with circular footprints that cannot control instantly their pose. Inhere, a self-balanced dual-wheeled differential drive system is used to explore the place. The system is equipped with linear accelerometers and angular gyroscopes, a 3D-LiDAR, and a forward-facing RGB-D camera. The system performs RTAB-SLAM using the IMU and the LiDAR, while the camera is used for loop closures. The mobile agent explores the planar space using a safe skeleton approach that places the agent as far as possible from the static obstacles. During the exploration strategy, the heading is towards any offered openings of the space. This space exploration strategy has as its highest priority the agent's safety in avoiding the obstacles followed by the exploration of undetected space. Experimental studies with a ROS-enabled mobile agent are presented indicating the path planning strategy while exploring the space.

Problem

• Safe exploration strategy for cluttered indoor environments
• Obstacle avoidance for non-holonomic circular footprint robots
• Real-time SLAM implementation using LiDAR and IMU sensors

Innovation

• SLAM-based safe skeleton exploration strategy
• Dual-wheeled differential drive with IMU and LiDAR
• RGB-D camera for loop closure detection