When every second counts: Multi-drone navigation in GPS-denied environments

本研究的目的是为多个无人机（UAV）开发一个框架，平衡信息共享，探索，定位，绘图和其他规划目标，从而允许一个团队的UAVs在复杂的环境中在时间紧迫的情况下导航。该项目希望通过将同时定位和映射（SLAM）算法与部分可观察马尔可夫决策过程（POMDP）和深度强化学习相结合，使用创新方法生成无人机导航的新知识。这将带来巨大的好处，例如在倒塌的建筑物或地下矿井内进行更灵敏的搜索和救援，以及在树冠下进行快速目标探测和测绘。

The aim of this research is to develop a framework for multiple Unmanned Aerial Vehicles (UAV), that balances information sharing, exploration, localization, mapping, and other planning objectives thus allowing a team of UAVs to navigate in complex environments in time critical situations. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining Simultaneous Localization and Mapping (SLAM) algorithms with Partially Observable Markov Decision Processes (POMDP) and Deep Reinforcement learning. This should provide significant benefits, such as more responsive search and rescue inside collapsed buildings or underground mines, as well as fast target detection and mapping under the tree canopy.