Abstract
The main objective of this research is to develop and evaluate the performance of strategies for cooperative control of autonomous air vehicles that seek to gather information about a dynamic target environment, evade threats, and coordinate strikes against targets. The air vehicles are equipped with sensors to view a limited region of the environment they are visiting, and are able to communicate with one another to enable cooperation. They are assumed to have some “physical” limitations including possibly maneuverability limitations, fuel/time constraints and sensor range and accuracy. The developed cooperative search framework is based on two inter-dependent tasks: (i) on-line learning of the environment and storing of the information in the form of a “target search map”; and (ii) utilization of the target search map and other information to compute on-line a guidance trajectory for the vehicle to follow. We study the stability of vehicular swarms to try to understand what types of communications are needed to achieve cooperative search and engagement, and characteristics that affect swarm aggregation and disintegration. Finally, we explore the utility of using-biomimicry of social foraging strategies to develop coordination strategies.
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Passino, K. et al. (2002). Cooperative Control for Autonomous Air Vehicles. In: Murphey, R., Pardalos, P.M. (eds) Cooperative Control and Optimization. Applied Optimization, vol 66. Springer, Boston, MA. https://doi.org/10.1007/0-306-47536-7_12
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DOI: https://doi.org/10.1007/0-306-47536-7_12
Publisher Name: Springer, Boston, MA
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