This paper deals with vision-based closed-loop control schemes for collision avoidance as well as maintenance of clearance in a-priori unknown textured environments. These control schemes are based on fuzzy logic and employ a visual motion cue, we call the Visual Threat Cue (VTC) that provides some measure for a relative change in range as well as clearance between 3D surface and a fixated observer in motion. It is a collective measure obtained directly from the raw data of gray level images, is independent of the 3D surface texture and needs no optical flow information, 3D reconstruction, segmentation, feature tracking or preprocessing. This motion cue is scale-independent, rotation independent and is measured in [time-1] units. Design of a closed-loop conventional controller for vision based navigation tasks pose a problem as the system is complex and ill-defined. On the other hand fuzzy control which is closer in spirit to human thinking and can implement linguistically expressed heuristic control policies directly without any knowledge about the dynamics of the complex process. The fuzzy controllers were tested in real time using a 486-based Personal Computer and a camera capable of undergoing 6-DOF motion. Results are highly encouraging.
Citation: NIST Interagency/Internal Report (NISTIR) - 5637Report Number:
NIST Pub Series: NIST Interagency/Internal Report (NISTIR)
Pub Type: NIST Pubs
Active Vision, Collision Avoidance, Maintenance of Clearance, Robotics & Intelligent Systems, Unmanned Systems, Vision, Control, Visual Motion