Vision based Collaborative Localization for UAVs
This project focuses on presenting a collaborative localization pipeline that is applicable for two or more multirotor vehicles with a monocular camera as the only sensor required on each vehicle. Feature detection and matching are performed between the individual views, thus allowing for reconstruction of the surrounding environment which is then used for localizing the moving vehicles within a group. Communication between nearby vehicles can be performed at specific instants of time so as to refine the map as well as improve the position of the accuracy of the individual vehicles.
Thermal vision for UAVs
This project focuses on integrating thermal cameras for enhanced drone vision. The goal of the project is to successfully implement thermal camera vision on a drone where thermal vision will be a supplement to a normal camera. The camera combination will be studied to see where thermal camera fusion shines, after which possible applications can be explored.
Innovative mapping techniques for UAVs
We are also currently exploring innovative mapping techniques using drones. The goal of this project is to identify and map mosquito spawns. The use of drones and automation in this task greatly reduces the manpower and financial cost of reducing mosquito populations. The work may eventually be applied to test sites in developing countries, where mosquito borne illness is a major concern.
Our goal is to develop and deploy Autonomous Shuttles on Texas A&M Campus and other private campuses such as hotels, golf courses etc. To this end, we are interested in developing robust localization, mapping, obstacle avoidance and control algorithms.
Sign Detection with LIDAR
One required ability for autonomous vehicles is to correctly identify street signs. This project investigates the feasibility of using a LIDAR sensor to detect, and classify signs for autonomous vehicles. Current popular methods for sign detection are vision based, however, in case of low visibility, a LIDAR detection method can be used instead.
Drivers soon to be replaced by self-driving vehicles, and It is important to keep the communication between the vehicles and the pedestrians uninterrupted. This project aims to design a system to communicate with pedestrians visually and audibly.