This paper describes recent work in the field of computer vision and relates the results to the much broader class of smart sensors. The sensor requirements for an autonomous mobile robot capable of map building and path planning are described. We show that when the sensor input noise is taken into consideration, a conventional CCD array is unable to provide a robust representation of an object, such that the object can be recognised regardless of the scale of the image plane. In contrast to this, biological based retinal arrays are able to achieve this (within signal limits). The paper concludes with the perspective that all sensor systems are data dependent. This is of little concern if the sensor consists of a single element, but becomes more important as larger arrays (with broader selectivity) are fabricated. These sensors may have to emulate biological systems, in an analogous manner to a retinal camera.
Building smarter sensors - lessons learned from computer vision
2000-01-01
438258 byte
Conference paper
Electronic Resource
English
Building Smarter Sensors - Lessons Learned from Computer Vision
British Library Conference Proceedings | 2000
|British Library Online Contents | 2007
Automotive engineering | 2002
|Online Contents | 1994
Lessons Learned in Building the Ares Projects
NTIS | 2010
|