Reliable visual perception of surrounding vessels is essential for situational awareness and safe navigation of unmanned surface vehicles (USVs). In complex nearshore waterways, densely distributed ships, significant scale variations, and mutual occlusions can degrade onboard monocular visual information, resulting in...
A risk-aware framework linking geometry-aware error quantification with belief-space collision avoidance under a fixed four-anchor UWB configuration is presented and the feasibility of linking geometry-aware UWB error characterization with belief-space safety constraints for UWB-localized quadrotor navigation is indica...
A physics-aware, end-to-end deep reinforcement learning (DRL) approach that acts directly on low-level body inputs, total thrust and body torques, and closes the loop through a high-fidelity Simulink environment is investigated.
Yaohua Shen, W. Chan· arXiv.org· 0 citations
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