A general dynamic vision architecture for UGV and UAV

Abstract

The expectation-based 4D approach to dynamic machine vision exploiting integral spatiotemporal models of objects in the real world is discussed in the application domains of unmanned ground and air vehicles. The method has demonstrated superior performance over the last half decade in autonomous road vehicle guidance with three different vans and busses, with an AGV on the factory floor and with completely autonomous relative state estimation for a twin turboprop aircraft in the landing approach to a runway without any external support; in all application areas only a small set of conventional microcomputers was sufficient for realizing the system. This shows the computational efficiency of the method combining both conventional engineering type algorithms and artificial intelligence components in a well balanced way.The modularity of the approach is demonstrated in a simulation set-up serving both the ground-and the air vehicle applications. Experimental results in both areas are discussed.

Cognition in Systems

“…s applying fuzzy rule s, constraints, e tc. Brooks & Stein, 1994;Dickmanns, 1992Dickmanns, , 1994Holyoak & Spe llman, 1993;Le nat & Brown, 1984;Ne umann, 1992;Nilsson, 1982;Rade rm ache r, 1991;Richter, 1989; . W inston, 1992; Z imme rmann, 1993 .…”

“…tonomous road vehicle s, see Dickmanns 1992Dickmanns , 1994 , whe re the author discusse s a possible solution for what he calls``the missing link be twe e n differe ntial e quation ] based e ngine e ring-type me thods and the artificial .…”

“…In fact, Kalman's pre dictions e rror fe e dback and the image se que nce proce ssing in Dickmanns 1992, .…”

Attention links sensing to recognition

“…Those who build complete vision application systems invoke attentional mechanisms because they must confront and defeat the computational load in order to achieve the goal of real-time processing (there are many examples, two of them being [11,12]). But the mainstream of computer vision does not give attentive processes, especially task-directed attention, much consideration.…”

Advanced visual surveillance using Bayesian networks

“…However, it is the intelligent, dynamic scene and event discrimination which lies at the heart of advanced vision systems. Developing a systematic methodology for the design, implementation and integration of such s y stems is currently a very important research p r o b l e m 3,5,14,30,40]. These methods must take i n to account the fact that vision is a computationally di cult problem as information available in the image does not provide a one-to-one mapping to physical objects in space.…”