Uncertainty based online planning for UAV missions in GPS-denied and cluttered environments
作者： Fernando Vanegas Alvarez
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摘要: This research is a novel approach to enabling Unmanned Aerial Vehicle (UAV) navigation and target finding tracking missions under uncertainty in cluttered GPS-denied environments. A framework, implemented as modular system, formulates the online Partially Observable Markov Decision Processes (POMDP). The POMDP computes motion policy that balances multiple mission objectives optimally. updated while flying based onboard sensor observations. provides an technology for UAV such search rescue, biodiversity assessment, underground mining infrastructure inspection challenging natural
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