Authors:
Francisco Bonin-Font
;
Alberto Ortiz
and
Gabriel Oliver
Affiliation:
University of the Balearic Islands, Spain
Keyword(s):
Mobile robots, Vision, Obstacle Avoidance, Feature Tracking, Inverse Perspective Transformation, SIFT.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Mobile Robots and Autonomous Systems
;
Robotics and Automation
Abstract:
This paper describes a new vision-based reactive navigation strategy addressed to mobile robots, comprising obstacle detection and avoidance. Most of the reactive vision-based systems base their strength uniquely on
the computation and analysis of quantitative information. The proposed algorithm combines a quantitative process with a set of qualitative rules to converge in a robust technique to safely explore unknown environments.
The process includes a feature detector/tracker, a new feature classifier based on the Inverse Perspective Transformation which discriminates between object and floor points, and a qualitative method to determine
the obstacle contour, their location in the image, and the course that the robot must take. The new strategy has been implemented on mobile robots with a single camera showing promising results.