At FRPG we study perception and control of autonomous aerial robots. We also develop novel aerial platforms to solve challenging real-world problems.

Aerial Perception: State-of-the-art deep neural network (DNN) based methods can solve a number of perception problems like detection, classification and identification. We develop novel DNN-based methods that can be deployed on small computing hardware suitable for aerial platforms, and can run on-board and in real-time. To this end, our methods leverage communication between multiple aerial robots as well as contextual knowledge such as mutual observation of the same target.  

Novel Aerial Platforms: Certain real world problems, such as monitoring animals in their natural habitat, require aerial platforms that are relatively silent and can operate for longer duration without needing to recharge. To this end, we develop small autonomous airships (<10m) that satisfy the above needs while being able to carry payloads up to 1kg, sufficient to deploy an on-board camera and a computer with GPU.