Detecting obstacles and drop-offs using stereo and motion cues for safe local motion

— 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 dropoffs, e.g., sidewalk curbs, downward stairs, and other hazards where an error could lead to disastrous consequences. In this paper, we propose algorithms for detecting both obstacles and drop-offs (also called negative obstacles) in an urban setting using stereo vision and motion cues. We propose a global color segmentation stereo method and compare its performance at detecting hazards against prior work using a local correlation stereo method. Furthermore, we introduce a novel drop-off detection scheme based on visual motion cues that adds to the performance of the stereo-vision methods. All algorithms are implemented and evaluated on data obtained by driving a mobile robot in urban environments.

• Type: Conference
• Year: 2008
• Where: IROS
• Authors: Aniket Murarka, Mohan Sridharan, Benjamin Kuipers
• Keywords: IROS 2008, Mobile Robot, Motion Cues, Robotics, Urban Environments