This paper presents a low cost strategy for real-time estimation of the position of obstacles in an unknown environment for autonomous robots. The strategy was intended for use in autonomous service robots, which navigate in unknown and dynamic indoor environments. In addition to human interaction, these environments are characterized by a design created for the human being, which is why our developments seek morphological and functional similarity equivalent to the human model. We use a pair of cameras on our robot to achieve a stereoscopic vision of the environment, and we analyze this information to determine the distance to obstacles using an algorithm that mimics bacterial behavior. The algorithm was evaluated on our robotic platform demonstrating high performance in the location of obstacles and real-time operation.
Collaboration network of the authors
11 authors ·
17 co-authorship links
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
Universidad Distrital Francisco José de Caldas
Affiliation unknown
Different organisations
Same organisation
Affiliation unknown
Thicker line = more joint articles · bigger circle = more articles
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.