Step and curb detection for autonomous vehicles with an algebraic derivative-based approach applied on laser rangefinder data

Abstract : Personal Mobility Vehicles (PMV) is is an important part of the Intelligent Transportation System (ITS) domain. These new transport systems have been designed for urban traffic areas, pedestrian streets, green zones and private parks. In these areas, steps and curbs make the movement of disable or mobility reduced people with PMV, and with standard chair wheels difficult. In this paper, we present a step and curb detection system based on laser sensors. This system is dedicated to vehicles able to cross over steps, for transportation systems, as well as for mobile robots. The system is based on the study of the first derivative of the altitude and highlights the use of a new algebraic derivative method adapted to laser sensor data. The system has been tested on several real scenarios. It provides the distance, altitude and orientation of the steps in front of the vehicle and offers a high level of precision, even with small steps and challenging scenarios such as stairs.
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Contributor : Evangeline Pollard <>
Submitted on : Friday, July 5, 2013 - 1:44:40 PM
Last modification on : Thursday, August 2, 2018 - 12:02:03 PM
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Evangeline Pollard, Joshué Pérez Rastelli, Fawzi Nashashibi. Step and curb detection for autonomous vehicles with an algebraic derivative-based approach applied on laser rangefinder data. IEEE-IV 2013 - The 2013 IEEE Intelligent Vehicles Symposium, Jun 2013, Gold Coast, Australia. ⟨hal-00841669⟩

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