Visual-Inertial Odometry on Chip: An Algorithm-and-Hardware Co-design Approach
Autonomous navigation of miniaturized robots (e.g., nano/pico aerial vehicles) is currently a grand challenge for robotics research, due to the need of processing a large amount of sensor data (e.g., camera frames) with limited on-board computational resources. In this paper we focus on the design o...
Main Authors: | Zhang, Zhengdong, Suleiman, Amr AbdulZahir, Carlone, Luca, Sze, Vivienne, Karaman, Sertac |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
Format: | Article |
Language: | en_US |
Published: |
2017
|
Online Access: | http://hdl.handle.net/1721.1/109522 https://orcid.org/0000-0002-0619-8199 https://orcid.org/0000-0002-0376-4220 https://orcid.org/0000-0003-1884-5397 https://orcid.org/0000-0003-4841-3990 https://orcid.org/0000-0002-2225-7275 |
Similar Items
-
Navion: A Fully Integrated Energy-Efficient Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones
by: Suleiman, Amr AbdulZahir, et al.
Published: (2018) -
Navion: A 2-mW Fully Integrated Real-Time Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones
by: Suleiman, Amr, et al.
Published: (2021) -
Hardware for Machine Learning: Challenges and Opportunities
by: Sze, Vivienne, et al.
Published: (2017) -
An Energy-Efficient Hardware Implementation of HOG-Based Object Detection at 1080HD 60 fps with Multi-Scale Support
by: Sze, Vivienne, et al.
Published: (2015) -
Hardware for machine learning: Challenges and opportunities
by: Sze, Vivienne, et al.
Published: (2017)