Steering a mobile robot in real time

Mei C. Chuah; Claude L. Fennema Jr.

doi:10.1117/12.189121

13 October 1994 Steering a mobile robot in real time

Mei C. Chuah, Claude L. Fennema Jr.

Proceedings Volume 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision; (1994) https://doi.org/10.1117/12.189121
Event: Photonics for Industrial Applications, 1994, Boston, MA, United States

Abstract

Using computer vision for mobile robot navigation has been of interest since the 1960s. This interest is evident in even the earliest robot projects: at SRI International (`Shakey') and at the Stanford University (`Stanford Cart'). These pioneering projects provided a foundation for late work but fell far short of providing real time solutions. Since the mid 1980s, the ARPA sponsored ALV and UGV projects have established a need for real time navigation. To achieve the necessary speed, some researchers have focused on building faster hardware; others have turned to the use of new computational architectures, such as neural nets. The work described in this paper uses another approach that has become known as `perceptual servoing.' Previously reported results show that perceptual servoing is both fast and accurate when used to steer vehicles equipped with precise odometers. When the instrumentation on the vehicle does not give precise measurements of distance traveled, as could be the case for a vehicle traveling on ice or mud, new techniques are required to accommodate the reduced ability to make accurate predictions about motion and control. This paper presents a method that computes estimates of distance traveled using landmarks and path information. The new method continues to perform in real time using modest computational facilities, and results demonstrate the effects of the new implementation on steering accuracy.

Citation Download Citation

Mei C. Chuah and Claude L. Fennema Jr. "Steering a mobile robot in real time", Proc. SPIE 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, (13 October 1994); https://doi.org/10.1117/12.189121

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