Abstract
This paper describes a reactive navigation method for autonomous agents such as robots or actors in virtual worlds, based on novel dynamic tangent obstacle representations, resulting in exceptionally successful, geometrically sensitive navigation. The method employs three levels of abstraction, treating each obstacle entity as an obstacle-valued function; this treatment enables extraordinary flexibility without pre-computation or deliberation, applying to all obstacles regardless of shape, including non-convex, polygonal, or arc-shaped obstacles in dynamic environments. The unconventional levels of abstraction and the geometric details of dynamic tangent representations are the primary contributions of this work, supporting smooth navigation even in scenarios with curved shapes, such as circular and figure-eight shaped tracks, or in environments requiring complex, winding paths.
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© 2011 Springer-Verlag Berlin Heidelberg
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Aaron, E., Mendoza, J.P. (2011). Dynamic Obstacle Representations for Robot and Virtual Agent Navigation. In: Butz, C., Lingras, P. (eds) Advances in Artificial Intelligence. Canadian AI 2011. Lecture Notes in Computer Science(), vol 6657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21043-3_1
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DOI: https://doi.org/10.1007/978-3-642-21043-3_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21042-6
Online ISBN: 978-3-642-21043-3
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