title: Robust navigation in an unknown environment with minimal sensing and representation.
abstract: This paper presents muNav, a novel approach to navigation which, with minimal requirements in terms of onboard sensory, memory, and computational power, exhibits way-finding behaviors in very complex environments. The algorithm is intrinsically robust, since it does not require any internal geometrical representation or self-localization capabilities. Experimental results, performed with both simulated and real robots, validate the proposed theoretical approach.
authors.affiliation: Department of Communication, Computer, and System Sciences, University of Genova, 16145 Genova, Italy. fulvio.mastrogiovanni@unige.it
authors.forename: Fulvio
authors.initials: F
authors.lastname: Mastrogiovanni
authors.forename: Antonio
authors.initials: A
authors.lastname: Sgorbissa
authors.forename: Renato
authors.initials: R
authors.lastname: Zaccaria
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D004777:Environment; D009038:Motion; D015203:Reproducibility of Results; D012371:Robotics / Q000379:methods*