Detecting obstacles and drop-offs using stereo and motion cues for safe local motion (2008)
A mobile robot operating in an urban environment has to navigate around obstacles and hazards. Though a significant amount of work has been done on detecting obstacles, not much attention has been given to the detection of drop-offs and other hazards where an error could lead to disastrous consequences. In this paper, we propose algorithms for detecting obstacles and drop-offs using stereo-vision and motion cues. We propose a color segmentation stereo method and compare its performance at detecting hazards with prior work using a correlation stereo method. Furthermore, we introduce a novel drop-off detection scheme based on motion cues that adds to the performance of the stereo-vision methods. All algorithms are implemented and tested on a physical robot platform in real urban environments.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-08) 2008.

Benjamin Kuipers Formerly affiliated Faculty kuipers [at] cs utexas edu
Aniket Murarka Ph.D. Alumni aniket [at] cs utexas edu
Mohan Sridharan Ph.D. Alumni mhnsrdhrn [at] gmail com