title: Radar Sensing for Intelligent Vehicles in Urban Environments.
abstract: Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successfully in dusty, foggy, blizzard-blinding, and poorly lit scenarios. This paper presents a novel method for ground and obstacle segmentation based on radar sensing. The algorithm operates directly in the sensor frame, without the need for a separate synchronised navigation source, calibration parameters describing the location of the radar in the vehicle frame, or the geometric restrictions made in the previous main method in the field. Experimental results are presented in various urban scenarios to validate this approach, showing its potential applicability for advanced driving assistance systems and autonomous vehicle operations.
authors.affiliation: Department of Engineering for Innovation, University of Salento, via Arnesano, 73100 Lecce, Italy. giulio.reina@unisalento.it.
authors.forename: Giulio
authors.initials: G
authors.lastname: Reina
authors.affiliation: Australian Centre for Field Robotics, University of Sydney, Rose Street Building (J04), 2006 Sydney, Australia. d.johnson@acfr.usyd.edu.au.
authors.forename: David
authors.initials: D
authors.lastname: Johnson
authors.affiliation: Australian Centre for Field Robotics, University of Sydney, Rose Street Building (J04), 2006 Sydney, Australia. j.underwood@acfr.usyd.edu.au.
authors.forename: James
authors.initials: J
authors.lastname: Underwood
keywords: navigation systems; perception in urban environment; radar sensing; robotic intelligent vehicles; unmanned ground vehicles