The lure of using motion vision as a fundamental element in the perception of space drives this effort to use flow 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 2-D image sequence; no 3-D reconstruction is attempted. Active mechanical gaze stabilization simplifies the visual interpretation problems by reducing camera rotation. By combining corridorfollowing and dead-end deflection, the robot has wandered around the lab at 30 cm/s for as long as 20 minutes without collision. The ability to support this behavior in real-time with current equipment promises expanded capabilities as computational power increases in the future.

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This paper discusses the integration of vision and touch sensors in a coordinate measuring machine (CMM) controller used for dimensional inspection tasks. A real-time hierarchical control system is presented in which a vision system extracts positions of features on a part to be inspected, and then guides a touch probe to efficiently measure these features. The probe is tracked by the vision system as it scans surfaces so that it's motion can be visually servoed. Minimalist sensorderived representations, involving only task-specific information, are used in this process. Although the camera itself remains uncalibrated, a real-time calibration of very limited scope is performed each processing cycle to transform the task-specific image information into 3-D information used as feedback to guide the probe.

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