2009 Poster Sessions : Autonomous Indoor Helicopter Flight using a Single Onboard Camera

Student Name : Sai Prashanth, Arvind Sujeeth
Advisor : Andrew Ng
Research Areas: Artificial Intelligence
We consider the problem of autonomously flying a helicopter in indoor environments. Navigation in indoor settings poses two major challenges. First, real-time perception and response is crucial because of the high presence of obstacles. Second, the limited free space in such a setting places severe restrictions on the size of the aerial vehicle, resulting in a frugal payload budget. We autonomously fly a miniature RC helicopter in small known environments using an on-board light-weight camera as the only sensor. We combine computer vision algorithms with a non-parametric learning algorithm on the images captured by the camera to achieve real-time 3D localization and navigation. We perform successful autonomous test flights along trajectories in two different indoor settings. Our results demonstrate that our method is capable of autonomous flight even in narrow indoor spaces with sharp corners and obstacles.

Sai Prashanth is a first year graduate student in Electrical Engineering at Stanford University. He works in the AI Lab with Andrew Ng, repairs broken helicopters and has recently moved on with life and started working on the Stanford AI Robot. He graduated with a B.Tech in Computer Science and Engineering from the Indian Institute of Technology at Kharagpur, India in 2008.

Arvind Sujeeth is a first year grad student and joined Electrical Engineering at Stanford University in Fall 2008. He works with Andrew Ng and Kunle Olukotun at Stanford. He completed his BS in Electrical and Computer Engineering from the University of Texas at Austin.