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Abstract: Laser scanners are omnipresent in robotic applications. Their measurements are used in many scenarios for robust map building, localization, collision avoidance, etc. But regarding the required precise measurement and mechanical system a laser scanner is quite expensive. Hence the robotic community is looking for alternative sensors. Since 2010 a new 3D sensor system - Microsoft Kinect [1] - developed for computer games is available and applied in robotic applications. With an appropriate filter... View more
Abstract:
Laser scanners are omnipresent in robotic applications. Their measurements are used in many scenarios for robust map building, localization, collision avoidance, etc. But regarding the required precise measurement and mechanical system a laser scanner is quite expensive. Hence the robotic community is looking for alternative sensors. Since 2010 a new 3D sensor system - Microsoft Kinect [1] - developed for computer games is available and applied in robotic applications. With an appropriate filter tool-chain its output can be mapped to a 2D laser scanner measurement. The reduced data set is ready to be processed by the established algorithms and methods developed for laser scanners. But will the Kinect sensor replace laser scanners in robotic applications? This paper compares the technical parameters of the new sensor with established laser scanners. Afterwards we investigate the possibilities and limits of a Kinect for three common robotic applications - map building, localization and obstacle avoidance.
Date of Conference: 16-18 Nov. 2012
Date Added to IEEE Xplore: 07 January 2013
ISBN Information:
INSPEC Accession Number: 13248900
Publisher: IEEE
Conference Location: Magdeburg, Germany
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Contents
Contents

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I. Introduction

Each robotic application requires a reliable perception of the environment. The effort increases with the complexity of the tasks. In a well defined scenario without unexpected situations (encapsulated industrial manipulators) a limited sensor configuration guarantees a correct and reliable behavior. An autonomously navigating system which moves in complex (everyday) scenarios and interacts with humans has to monitor much more aspects of the environment. The related tasks in service robot applications demand different sensor requirements. For a collision avoidance a complete coverage of the area around the robot is important. In contrast, many localization algorithms do not need a complete “panorama view” but depend on representative number of samples. As a last example, the sensors of a gripper have to provide a precise contour of the object that has to be manipulated.

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