Tsung-Wun WangHAN-PANG HUANGYu-Lin Zhao2025-05-152025-05-152025-03https://www.scopus.com/record/display.uri?eid=2-s2.0-86000539671&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/729298This paper presents a 3D vision-based autonomous navigation system for wheeled mobile robots equipped with an RGB-D camera. The system integrates SLAM (simultaneous localization and mapping), motion planning, and obstacle avoidance to operate in both static and dynamic environments. A real-time pipeline is developed to construct sparse and dense maps for precise localization and path planning. Navigation meshes (NavMeshes) derived from 3D reconstructions facilitate efficient A* path planning. Additionally, a dynamic “U-map” generated from depth data identifies obstacles, enabling rapid NavMesh updates for obstacle avoidance. The proposed system achieves real-time performance and robust navigation across diverse terrains, including uneven surfaces and ramps, offering a comprehensive solution for 3D vision-guided robotic navigation.3D vision-based navigationmesh reconstructionnavigation mesh (NavMesh)obstacle avoidanceSLAM[SDGs]SDG11journal article10.3390/app15052323