Nik-V9/HEAPUtil

Code for the RA-L (IROS) 2021 paper "A Hierarchical Dual Model of Environment- and Place-Specific Utility for Visual Place Recognition"

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This project helps robots and autonomous vehicles accurately determine their location in diverse, real-world environments by matching current camera views against a stored map. It takes sequences of images, often captured in different seasons or lighting conditions, and processes them to identify specific visual cues. The output is a highly reliable estimate of the robot's current position, ideal for engineers developing robust navigation systems for autonomous platforms.

No commits in the last 6 months.

Use this if you need to improve a robot's ability to recognize its precise location using visual data, especially when dealing with changes in the environment like varying weather or time of day.

Not ideal if your primary goal is object detection or general image classification, as this tool is specifically designed for visual place recognition and localization.

robot-navigation autonomous-vehicles visual-localization robotics-engineering environmental-perception
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 11 / 25

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Stars

70

Forks

7

Language

Python

License

MIT

Last pushed

Feb 19, 2023

Commits (30d)

0

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