1. Multi-drone Estimation and Intelligent Decision making framework
Design efficient multi-drone estimation and decision-making techniques for: a) estimating the states of multiple objects of interest in uncertain disaster environments (e.g., with noisy measurements) and b) optimally taking decisions under uncertainty.
2. Multi-drone Cooperative Guidance and Planning
Design intelligent guidance and planning techniques that will enable a team of cooperative agents to efficiently navigate the mission space of challenging disaster environments.
3. Multi-drone Indoor and Outdoor Mapping, Exploration, and Inspection
Design efficient methodologies for multi-drone mapping, exploration, and inspection. Develop optimal strategies for multi-drone exploration aimed at achieving specific mission objectives. The proposed approach should be designed to maximize the area explored collaboratively by the drone swarm while simultaneously reducing the total exploration time.
4. Wildfire cooperative monitoring
Design algorithms that will enable a team of flying agents equipped with proper hardware for localization and fire detection (e.g., GPS, IMU, high-resolution camera) to monitor in real-time the wildfire evolution and continuously update the mission control with the fire state.
5. Wildfire spread model learning
Investigate how a team of cooperative autonomous agents can learn the wildfire spread model and how to use this model for better fire monitoring and decision making.
6. Real time situational awareness
Design methods for effective monitoring of assets and resources including first responders and means during large-scale disaster situations. Implement risk inference techniques to guide first responders promptly and continuously to safe operating areas while maximizing their performance in the field.
7. Fault-Tolerant Operation
Devise fault-tolerant planning and control techniques that address various types of faults occurring during planning and execution, such as those encountered in wildfire monitoring and coverage tasks. We aim to explore how different stochastic disturbances (e.g., disturbances arising from various probability distributions) can be integrated into the planning process to ensure robust operation. This approach will enable the system to predict and, to some extent, anticipate persistent disturbances during real-time operations, thereby enhancing fault tolerance and ensuring mission continuity.
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