When every second counts: Multi-drone navigation in GPS-denied environments. 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 Localizatio ....When every second counts: Multi-drone navigation in GPS-denied environments. 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. Read moreRead less
Difficulties of monitoring for rare events. This project aims to identify cognitive and neural processes involved in sustaining attention to moving displays under monitoring conditions.People are poor at monitoring for rare events: they tend to miss infrequent targets. This is a problem in automated systems for transport, rail and air traffic control. If a computer error occurs, the operator needs to intervene quickly. This project will develop a tool for studying monitoring and determine patter ....Difficulties of monitoring for rare events. This project aims to identify cognitive and neural processes involved in sustaining attention to moving displays under monitoring conditions.People are poor at monitoring for rare events: they tend to miss infrequent targets. This is a problem in automated systems for transport, rail and air traffic control. If a computer error occurs, the operator needs to intervene quickly. This project will develop a tool for studying monitoring and determine patterns of brain activity that predict a lapse of attention. The results should contribute to theories of vigilance and improve performance in real-world monitoring situations.Read moreRead less