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Novel Active-Vision-Based Motion Cues for Local Navigation

Published

Author(s)

S R. Kundur, Daniel Raviv

Abstract

In the absence of a-priori information about the environment, an autonomous mobile robot relies on sensory information to make local judgments about its surrounding. Generation of a local collision-free path based on sensory data plays an important role in the control of the robot¿s interaction with the environment. This paper presents a novel approach based on active-vision paradigm, for generating local collision-free paths for mobile robot navigation, in indoor as well as outdoor environments. Two measurable visual motion cues that provide, some measure for a relative change in range as well clearance between a 3D surface and a fixated observer in motion are described. These visual cues are independent of the 3D environment and need no a-priori knowledge about it. For each visual motion cue, there is a visual field surrounding the moving observer. In other words, there are imaginary 3D surfaces attached to the observer that move with it, each of which correspond to a value of the cue. These visual fields can be used to demarcate regions around a moving observer into safe and danger zones of varying degree, which is suitable for making local decisions about the steering as well as speed commands to the mobile robot. We describe a practical method to extract these cues from a sequence of images. This approach needs no feature tracking between images and almost no camera calibration.
Citation
NIST Interagency/Internal Report (NISTIR) - 5791
Report Number
5791

Keywords

Unmanned Systems, Vision, Mobility, active vision, visual navigation, collision avoidance, clearance

Citation

Kundur, S. and Raviv, D. (1996), Novel Active-Vision-Based Motion Cues for Local Navigation, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=820557 (Accessed April 14, 2024)
Created January 31, 1996, Updated October 12, 2021