CDDT: Fast Approximate 2D Ray Casting for Accelerated Localization

© 2018 IEEE. Localization is an essential component for autonomous robots. A well-established localization approach combines ray casting with a particle filter, leading to a computationally expensive algorithm that is difficult to run on resource-constrained mobile robots. We present a novel data st...

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Bibliographic Details
Main Authors: Walsh, Corey H. (Author), Karaman, Sertac (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2021-11-09T13:28:52Z.
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Online Access:Get fulltext
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100 1 0 |a Walsh, Corey H.  |e author 
700 1 0 |a Karaman, Sertac  |e author 
245 0 0 |a CDDT: Fast Approximate 2D Ray Casting for Accelerated Localization 
260 |b Institute of Electrical and Electronics Engineers (IEEE),   |c 2021-11-09T13:28:52Z. 
856 |z Get fulltext  |u https://hdl.handle.net/1721.1/137859 
520 |a © 2018 IEEE. Localization is an essential component for autonomous robots. A well-established localization approach combines ray casting with a particle filter, leading to a computationally expensive algorithm that is difficult to run on resource-constrained mobile robots. We present a novel data structure called the Compressed Directional Distance Transform for accelerating ray casting in two dimensional occupancy grid maps. Our approach allows online map updates, and near constant time ray casting performance for a fixed size map, in contrast with other methods exhibit poor worst case performance. Our experimental results show that the proposed algorithm approximates the performance characteristics of reading from a three dimensional lookup table of ray cast solutions while requiring two orders of magnitude less memory and precomputation. This results in a particle filter algorithm which can maintain 2500 particles with 61 ray casts per particle at 40Hz, using a single CPU thread onboard a mobile robot. 
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655 7 |a Article 
773 |t 10.1109/ICRA.2018.8460743