A dynamic sensor placement algorithm for dense sampling

Vineet Bhatawadekar, Ravishankar Sivalingam, Nikolaos Papanikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For many applications, including robotic planning, obstacle avoidance, and mapping it has been observed with laser range-scanners and depth sensors that their sampling densities, i.e., the number of range measurements per unit length of the scanned contour, can vary greatly even within a single scan measurement. In this paper, an on-line placement algorithm is proposed that computes where the robot must next move so as to sample its environment uniformly and densely. The algorithm guarantees the minimum number of measurements per unit length of the observed space, obtaining a high and uniform spatial measurement density. It provides a Next-Best-View relative to a robot's current position while satisfying a locally-defined constraint function based on the sampling density of points. Three variants of this algorithm, suitable for different practical applications are demonstrated with experiments on real robots in interesting scenarios.

Original languageEnglish (US)
Title of host publicationIROS'11 - 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
Subtitle of host publicationCelebrating 50 Years of Robotics
Pages1167-1172
Number of pages6
DOIs
StatePublished - Dec 29 2011
Event2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: Celebrating 50 Years of Robotics, IROS'11 - San Francisco, CA, United States
Duration: Sep 25 2011Sep 30 2011

Publication series

NameIEEE International Conference on Intelligent Robots and Systems

Other

Other2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: Celebrating 50 Years of Robotics, IROS'11
CountryUnited States
CitySan Francisco, CA
Period9/25/119/30/11

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