Integrating swarm intelligence with bayesian networks for continuous UAV-based surveillance in dynamic environments

The loss of wildlife due to illegal poaching activity poses threats on both the survival of iconic animal species and the livelihood of local communities. This research proposes a distributed surveillance model in which a UAV swarm autonomously coordinates continuous surveillance in a dynamic environment. The adaptive behaviour of poachers has...

Potential Field Methods for Safe Reinforcement Learning: Exploring Q-Learning and Potential Fields

A Reinforcement Learning (RL) agent learns about its environment through exploration. For most physical applications such as search and rescue UAVs, this exploration must take place with safety in mind. Unregulated exploration, especially at the beginning of a run, will lead to fatal situations such as crashes. One approach to mitigating these...