Brief:
This project involves some designs on UAV interacting with animals. The first work is about shark attack protection, the second work is about wild animal monitoring, and the third is about the herding of animals.
Shark attacks can make beach tourists anxious about sharing the ocean with apex predators. Although the raw number of shark attacks is deficient, the absolute terror caused by sharks is genuine. We propose to use drones to intervene and prevent shark attacks for protecting swimmers and surfers.
Protection of wild animals relies on understanding the interaction between the animals and their environment. With the ability to rapidly access rugged areas, aerial monitoring by drones is fast becoming a viable tool for ecologists to monitor wild animals. Unfortunately, this approach results in significant disturbance to different species of wild animals. Inspired by motion camouflage, we explore a navigation method for a drone to covertly observe a group of animals and their habitat.
The herding of animals mainly refers to driving a group of animals from one position to another. The current practice is to use herding dogs. We investigate the robotic herding by a fleet of drones and analyze its effectiveness via model-based simulations.
Published papers related to this project:Â
Xiaohui Li, Hailong Huang, Andrey V Savkin, A Novel Method for Protecting Swimmers and Surfers from Shark Attacks using Communicating Autonomous Drones, IEEE Internet of Things Journal, 2020.
Xiaohui Li, Hailong Huang, Andrey V Savkin, Autonomous Navigation of an Aerial Drone to Observe a Group of Wild Animals with Reduced Visual Disturbance, IEEE Systems Journal, 2021.
Xiaohui Li, Hailong Huang, Andrey V Savkin, Jian Zhang, Robotic Herding of Farm Animals Using a Network of Barking Aerial Drones, Drones. 2021