General Place Recognition
ICRA 2022 Competition
Competition Background
The ability of mobile robots to recognize previously visited or mapped areas is essential to achieving reliable autonomous systems. Place recognition for localization and SLAM is a promising method for achieving this ability. However, current approaches are negatively affected by differences in viewpoint and environmental conditions that affect visual appearance (e.g. illumination, season, time of day), and so these methods struggle to provide continuous localization in environments that change over time. These issues are compounded when trying to localize in large-scale (several-kilometer length) maps, where the effects of repeated terrain and geometries result in greater localization uncertainty. This competition aims to push visual and LiDAR state-of-the-art techniques for localization in large-scale environments, with an emphasis on environments with changing conditions.
To evaluate localization performance under long-term and large-scale tasks, we provide benchmark datasets to investigate robust re-localization under changing viewpoints and domain differences. This competition will include two challenges:
City-scale UGV Localization Dataset (3D-3D Localization)
Sign up website: https://www.aicrowd.com/challenges/icra2022-general-place-recognition-city-scale-ugv-localization
Visual Terrain Relative Navigation Dataset (2D-2D Localization)
Sign up website: https://www.aicrowd.com/challenges/icra2022-general-place-recognition-visual-terrain-relative-navigation
For the details, please refer to the dataset page.
Software Development Kit (SDK)
To accelerate the process of development, we provide a complete SDK for loading datasets and evaluating results. Python APIs are given so it would be convenient for participants to integrate and use the interfaces in their code, which include the API to:
Easy access to our datasets;
Evaluate metrics for visual/Lidar place recognition;
Submit results for online evaluation at crowdAI;
With this SDK, participants just need to focus on their algorithms and try to improve the place recognition accuracy.
The SDK is held in the Github repo: https://github.com/MetaSLAM/GPR_Competition
System Architecture of the MetaSLAM SDK
Schedule & Award
Dataset Open: 05/10/2022
1-round Competition: 05/10/2022~05/24/2022
Presentation at ICRA 2022
2-round Competition: 06/01/2022~09/01/2022
No1. in each track: $3000
No2. in each track: $2000
Excellent Competitors also have the chance to take the internship at CMU.
Sponsors
Talks
Talk Schedule 05/24/2022 EST time
9:30 AM - 10:15 AM Dr. Yimin Zhang
10:15 AM - 11:00 AM Prof. Luca Carlone
11:00 AM - 12:00 PM Competition Panel Discussion
13:00 PM - 13:45 PM Prof. Jun-Yan Zhu
13:45 PM - 14:30 PM Prof. Michael Milford
14:30 PM - 15:15 PM Dr. Ji Zhang
15:15 PM - 16:00 PM Prof. Sebastian Scherer
Organizers
Sebastian Scherer Associate Research Professor@CMU
Peng Yin Project Scientist @ CMU
Zhipeng Cai Research Scientist @Embodied AI Lab, Intel
Shiqi Zhao Master@UCSD
Ivan Cisneros Master@CMU
Guangzhao Li
Master@CMU
Haowen Lai Master@Tsinghua
Ruohai Ge Mater@CMU
Contact
Email: pyin2@andrew.cmu.edu
Tel: +1 (412)-320-5786