csiro-robotics/Wild-Places

🏞️ [IEEE ICRA2023] The official repository for paper "Wild-Places: A Large-Scale Dataset for Lidar Place Recognition in Unstructured Natural Environments" To appear in 2023 IEEE International Conference on Robotics and Automation (ICRA)

41
/ 100
Emerging

This project provides a large-scale dataset of Lidar scans from outdoor, natural environments. It helps robotics researchers and engineers test and improve algorithms that allow autonomous robots to recognize where they are in the world. You input raw Lidar data, and the algorithms output a recognized location, enabling the robot to navigate effectively.

Use this if you are developing or evaluating Lidar-based place recognition systems for robots operating in challenging, unstructured natural terrains.

Not ideal if you are working with indoor environments, structured urban settings, or need a dataset that focuses solely on visual (camera) place recognition.

robotics autonomous-navigation lidar-mapping localization robot-perception
No Package No Dependents
Maintenance 10 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 6 / 25

How are scores calculated?

Stars

95

Forks

3

Language

Python

License

Last pushed

Mar 04, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/csiro-robotics/Wild-Places"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.