5 papers
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation
Wenqi Bai, Shiliang Zhang, Xiaohui Zhang +4
The advancement in autonomous vehicles has empowered navigation and exploration in unknown environments. Geomagnetic navigation for autonomous vehicles has drawn increasing attenti…
Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation
Songnan Yang, Shiliang Zhang, Qianyun Zhang +2
Geomagnetic navigation leverages the ubiquitous Earth's magnetic signals to navigate missions, without dependence on GPS services or pre-stored geographic maps. It has drawn increa…
Geomagnetic and Inertial Combined Navigation Approach Based on Flexible Correction-Model Predictive Control Algorithm
Xiaohui Zhang, Xingming Li, Songnan Yang +2
This paper proposes a geomagnetic and inertial combined navigation approach based on the flexible correction-model predictive control algorithm (Fc-MPC). This approach aims to over…
Long-distance Geomagnetic Navigation in GNSS-denied Environments with Deep Reinforcement Learning
Wenqi Bai, Xiaohui Zhang, Shiliang Zhang +3
Geomagnetic navigation has drawn increasing attention with its capacity in navigating through complex environments and its independence from external navigation services like globa…
A Bionic Data-driven Approach for Long-distance Underwater Navigation with Anomaly Resistance
Songnan Yang, Xiaohui Zhang, Shiliang Zhang +4
Various animals exhibit accurate navigation using environment cues. The Earth's magnetic field has been proved a reliable information source in long-distance fauna migration. Inspi…