Real-time obstacle avoidance using central flow divergence, and peripheral flow

被引:70
作者
Coombs, D [1 ]
Herman, M [1 ]
Hong, TH [1 ]
Nashman, M [1 ]
机构
[1] Natl Inst Stand & Technol, Intelligent Syst Div, Gaithersburg, MD 20899 USA
来源
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION | 1998年 / 14卷 / 01期
关键词
active vision; digital control; feedback systems; image motion analysis; mobile robots; mobile robot motion planning; object identification; real time systems; recursive estimation; robot vision systems;
D O I
10.1109/70.660840
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The lure of using motion vision as a fundamental element in the perception of space drives this effort to use dow features as the sole cues for robot mobility, Real-time estimates of image flow and flow divergence provide the robot's sense of space. The robot steers down a conceptual corridor, comparing left and right peripheral flows, Large central flow divergence warns the robot of impending collisions at "dead ends." When this occurs, the robot turns around and resumes wandering. Behavior is generated by directly using flow-based information in the two dimensional (2-D) image sequence; no three-dimensional (3-D) reconstruction is attempted. Active mechanical gaze stabilization simplifies the visual interpretation problems by reducing camera rotation. By combining corridor following and dead-end deflection, the robot has wandered around the lab at 30 cm/s for as long as 20 min without collision. The ability to support this behavior in real-time with current equipment promises expanded capabilities as computational power increases in the future.
引用
收藏
页码:49 / 59
页数:11
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