Navigating under the forest canopy and in the urban jungle

该项目旨在为无人机（UAV）开发一个框架，以最佳地平衡定位，测绘和其他目标，以解决地图下的顺序决策任务和不确定性。该项目希望通过将同步定位和映射算法与部分可观察马尔可夫决策过程相结合的创新方法，在无人机导航中产生新的知识。该项目的预期结果将使无人机能够解决地图下的多个目标，并在gps拒绝的环境中构成不确定性。这将带来显著的好处，例如更灵敏的灾害管理、森林火灾监测和生物安全，以及改进的环境监测。

This project aims to develop a framework for unmanned aerial vehicles (UAV), which optimally balances localisation, mapping and other objectives in order to solve sequential decision tasks under map and pose uncertainty. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining simultaneous localisation and mapping algorithms with partially observable markov decision processes. The project’s expected outcomes will enable UAVs to solve multiple objectives under map and pose uncertainty in GPS-denied environments. This will provide significant benefits, such as more responsive disaster management, bushfire monitoring and biosecurity, and improved environmental monitoring.