Search-Free Gridding and Temporal Local Matching Based Observation for High Frame Rate and Ultra-Low Delay SLAM System
Year: 2018
Type: conference-paper
Abstract: Tracking of camera pose in simultaneous localization and mapping (SLAM) using particle filter has high potential of parallelism and is promising in high frame rate and ultra-low delay applications. However, heavy calculation and hardware-unfriendly algorithm in projection and matching which take 88.6% time consumption of particle filter become problems in acceleration. This paper proposes search-free gridding based redundant projection removal, non-iteration linear function based division, and temporal 2D local matching in particle filter based SLAM on FPGA. Search-free gridding based redundant projection removal removes dense map points and reduce projection times. Non-iteration linear function based division considers the particularly of projection problem in SLAM and achieve low delay partial division in projection. Temporal 2D local matching uses characteristic of high frame rate video and considers hardware implementation to realize a low delay local matching. The algorithm is tested on 762fps VGA (640480) indoor sequences. Software result shows that this algorithm has 1.20° error in rotation and 1.90 cm error in translation compared with ORB-SLAM. Hardware result shows that matching and projection have 0.457 ms latency processing 1000 feature points.
Authors: Yuchen Yang, Songlin Du, Takeshi Ikenaga
Institution: Waseda University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2907566640