CoSafe-Nav: An Intelligent Connectivity-Aware Navigation System for UAVs in Perception-Degraded Environments
Reliable UAV navigation is challenging when direct geometric perception is limited and only sparse environmental observations are available. This paper presents CoSafe-Nav, an integrated navigation framework that uses ultra-wideband (UWB) line-of-sight (LOS) observations to construct a candidate corridor and guide trajectory generation. The framework addresses fixed-altitude planar navigation with known, pre-deployed anchors and an available UAV pose estimate. LOS-supported segments are accumulated online, and a grid-based Euclidean distance transform (EDT) provides a common clearance representation for path ranking and trajectory refinement. The path planner combines travel distance with a local inverse-distance penalty. The trajectory stage corrects interior control points using the EDT gradient, regenerates the spatial curve, and assigns execution timing. Evaluation comprises two simulation scenarios, component comparisons, an anchor-availability study, and indoor UAV trials. CoSafe-Nav completed all ten navigation tasks in each simulation scenario and four of five indoor trials. In the path-planning comparison, mean EDT corridor clearance increased from 0.76 to 0.98 m and from 0.63 to 0.91 m, accompanied by longer routes. These means describe successful tasks within each configuration. The trajectory comparison also showed a lower acceleration integral for the safety-guided method. The results support the feasibility of the integrated processing chain under the stated pre-instrumented deployment conditions.
Authors
- Xueyong Xu (ORCID: https://orcid.org/0009-0004-6429-659X)
- Chenchen Fu (ORCID: https://orcid.org/0000-0002-6724-9594)
- Xiangxiang Xing
- Hengkai Zhong
- Yuhang Xu
- Xiang Liu
- Weiwei Wu
- Jinchen Wang
- Yan Lyu
Institutions
- China Aerospace Science and Industry Corporation (China) (CN)
- Southeast University (CN)
Publication Details
- Journal
- Symmetry
- Published
- 2026-09-27
- DOI
- https://doi.org/10.3390/sym18101613
- Primary Topic
- Robotic Path Planning Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00