A Safe 2D Grid Map for Indoor Wheelchair Navigation Using the LiDAR Camera System
Received: 16 May 2025 | Revised: 18 July 2025 | Accepted: 27 July 2025 | Online: 23 September 2025
Corresponding author: Thanh Hai Nguyen
Abstract
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.
Keywords:
safe 2D grid map, 3D point cloud map, smart wheelchair, ICP algorithm, LiDAR camera systemDownloads
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Copyright (c) 2025 Ba Viet Ngo, Thanh Hai Nguyen, Thanh Nghia Nguyen, Minh Chanh Cao
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