A Safe 2D Grid Map for Indoor Wheelchair Navigation Using the LiDAR Camera System - Ngo, Ba Viet; Nguyen, Thanh Hai; Nguyen, Thanh Nghia; Cao, Minh Chanh (Engineering, Technology & Applied Science Research, 2025)
Mobile robots are widely used in localization, mapping, and path planning, with map construction being essential for safe navigation. This study presents a method for creating a safe 2D grid map for indoor electric wheelchair navigation using a LiDAR-camera system. The process converts a 3D environmental map into a 2D grid map, helping the wheelchair detect obstacles at unsafe heights. First, a 3D environmental map is generated using the LiDAR-camera system of an iPhone 12 Pro, capturing 3D point clouds. The Iterative Closest Point (ICP) algorithm merges these point clouds into a complete 3D map. Accuracy is verified by comparing the distances between the real environment and the generated map, with deviations less than 2%. To enhance safety, points exceeding the wheelchair's height limit are removed, forming a refined 3D height map. This map is then projected into a 2D representation and overlaid with a grid, ensuring each cell matches the wheelchair's dimensions. A pixel density approximation refines the grid. The Q-learning method is applied for autonomous wheelchair navigation, proving the system's effectiveness in real indoor environments.