Ants, when walking around in cluttered environments, are known to follow a limited number of common routes. Research published in PLOS Computational Biology and led by Olivier Bertrand (Bielefeld University, Germany) shows that similar routes emerge when an algorithm for collision avoidance, based on the apparent motion of obstacles, is combined with a target direction.
The number of robots in our surroundings is increasing continually. They are used to rescue humans, inspect hazardous terrain, or clean our homes. Over the past few decades, they have become more autonomous, safer, and cheaper to build. Every autonomous robot needs to navigate in complex environments without colliding with obstacles along its route.
Flying insects are able to solve this task by mainly relying on vision, extracting object distances from the motion of the environment on their retina when moving. However, trying to accomplish the extraction of distance with movement detectors found in the animal kingdom is tricky because they do not provide unambiguous velocity information, but are much affected also by the textural properties of the environment.
In the article a parsimonious algorithm to avoid collisions in challenging environments solely based on bio-inspired so-called elementary motion detectors has been introduced. Moreover, the trajectories resulting from the coupling of this algorithm with a goal direction leads to an interesting goal-directed behavior, namely the formation of a small number of routes, like those observed in navigating insects.
Image Credit:Bertrand et al.
All works published in PLOS Computational Biology are Open Access, which means that all content is immediately and freely available. Use this URL in your coverage to provide readers access to the paper upon publication: http://journals.
University Bielefeld & CITEC
Postfach 10 01 31
Bielefeld, NRW 33501
Citation: Bertrand OJN, Lindemann JP, Egelhaaf M (2015) A Bio-inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes. PLoS Comput Biol 11(11): e1004339. doi:10.1371/journal.pcbi.1004339
Funding: The project is funded by the Deutsche Forschungsgemeinschaft (DFG). The publication fee has been paid by the Deutsche Forschungsgemeinschaft and the Open Access Publication Funds of Bielefeld University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
About PLOS Computational Biology
PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. All works published in PLOS Computational Biology are Open Access. All content is immediately available and subject only to the condition that the original authorship and source are properly attributed. Copyright is retained. For more information contact email@example.com.
PLOS is a nonprofit publisher and advocacy organization founded to accelerate progress in science and medicine by leading a transformation in research communication. For more information, visit http://www.