Naroditsky, O., Zhu, Z. Das, A., Samarasekera, S., Oskiper, T., & Kumar, R., (June 2009). “VideoTrek: A vision system for a tag-along robot,” Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, vol., no., pp.1101,1108, 20-25.
Abstract
We present a system that combines multiple visual navigation techniques to achieve GPS-denied, non-line-of-sight SLAM capability for heterogeneous platforms. Our approach builds on several layers of vision algorithms, including sparse frame-to-frame structure from motion (visual odometry), a Kalman filter for fusion with inertial measurement unit (IMU) data and a distributed visual landmark matching capability with geometric consistency verification. We apply these techniques to implement a tag-along robot, where a human operator leads the way and a robot autonomously follows. We show results for a real-time implementation of such a system with real field constraints on CPU power and network resources.
