A New Approach to ORB Acceleration Using a Modern Low-Power Microcontroller
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View abstract on PubMed
Summary
This summary is machine-generated.This study explores using microcontrollers for Oriented FAST and Rotated BRIEF (ORB) feature extraction in visual Simultaneous Location And Mapping (SLAM) systems. While slower than hardware acceleration, it offers a lower-power, cost-effective alternative for specific applications.
Area Of Science
- Computer Vision
- Robotics
- Embedded Systems
Background
- Feature extraction and description are crucial for visual Simultaneous Location And Mapping (SLAM) systems.
- Oriented FAST and Rotated BRIEF (ORB) is a common but computationally intensive algorithm used in SLAM.
- Hardware acceleration (FPGAs, ASICs) is a typical solution but increases costs.
Purpose Of The Study
- To propose and evaluate a feature extraction and description solution using a low-power microcontroller.
- To analyze the execution time and power consumption of the ORB algorithm on a microcontroller.
- To assess the viability of microcontroller-based ORB for SLAM applications.
Main Methods
- Implementation of the ORB algorithm on a modern low-power microcontroller.
- Analysis of ORB execution time varying feature points and internal variables.
- Measurement of power consumption during ORB execution.
Main Results
- ORB execution time reached a maximum of 0.6 seconds for 1241 × 376 resolution images.
- Power consumption ranged between 30 and 40 milliwatts.
- The microcontroller-based solution is slower than hardware acceleration but viable for certain applications.
Conclusions
- A microcontroller-based ORB implementation offers a lower-power and more economical alternative to hardware acceleration for SLAM.
- The performance is suitable for applications where real-time constraints are less stringent.
- Further optimizations can enhance the performance of microcontroller-based ORB for SLAM.
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