PttAcc: Pipeline-Based Taylor Expansion Fitting Arctangent Angle Hardware Accelerator Design for Descriptor Duty in ORB-SLAM System
In simultaneous localization and mapping (SLAM), the oriented FAST and rotated BRIEF (ORB) algorithm is key for feature detection and description, but its computational demands, particularly in arctangent angle computation, hinder real-time use on embedded systems. To solve this, we introduce PttAcc, a hardware accelerator using pipeline architecture and the Taylor expansion fitting algorithm. Our simulations show PttAcc significantly accelerates arctangent computation while maintaining accuracy, reducing total area by 82.56% and power consumption by 63.49% compared to coordinate rotation digital computer (CORDIC) components. It achieves a performance acceleration ratio of 15.8 and speeds up descriptor tasks by up to 4.3 times.
Authors
- Peiyuan Wan (ORCID: https://orcid.org/0000-0003-4875-6432)
- Chongfei Shen
- Dejian Li (ORCID: https://orcid.org/0009-0001-0547-2264)
- Zhijie Chen (ORCID: https://orcid.org/0000-0003-3988-6446)
- Fei Xiao
- Meng Liu (ORCID: https://orcid.org/0000-0002-6803-0789)
- Ruijie Wang (ORCID: https://orcid.org/0009-0005-5770-0862)
Institutions
- Beijing University of Technology (CN)
- Beijing Microelectronics Technology Institute (CN)
Publication Details
- Journal
- IEEE Embedded Systems Letters
- Published
- 2024-10-03
- DOI
- https://doi.org/10.1109/les.2024.3472731
- Primary Topic
- Parallel Computing and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00