Challenge Protocol
Overview
The tasks which participants will tackle in this challenge are divided into separate stages:
- Pre-Stage: A qualification phase in simulation, where the objective is to pick up a cube and move it on a given trajectory.
- Stage 1: Participants who passed the pre-stage will be granted access to the robots and will be required to solve the same task but now on the real robots.
- Stage 2: In the last stage, the cube is replaced by multiple, identical dice, which have to arranged in specific patterns.
Participants will use the robots similarly to a cluster. They can submit jobs, where each job corresponds to executing an episode on a real robot. After termination, participants will have access to the data generated during that episode (all the sensory data and actions taken).
The code will be executed in a Singularity (similar to Docker) image, in which participants can install additional software and test their code in simulation. For this purpose, we provide a simulator with an identical interface as the real robots.
Prizes
In each of the two stages, the following prizes are awarded to the participants with the best scores.
Stage 1:
- Winner: 3,000 EUR
- Runner-up: 1,500 EUR
- Third-place: 1,000 EUR
- Best Paper: 3,000 EUR
- Runner-up best paper: 1,500 EUR
Phase 3:
- Winner: 3,000 EUR
- Runner-up: 1,500 EUR
- Third-place: 1,000 EUR
- Best Paper: 3,000 EUR
- Runner-up best paper: 1,500 EUR
Important: In order to receive prize money, winning teams are required to publish their report and source code under an open source license.
The pre-stage is not awarded any prizes and just serves as a qualification round.
Pre-Stage (Simulation)
Anyone can participate, no registration is required at the beginning of this phase. Participants can simply download a publicly available repository containing the simulator (instructions coming soon).
The goal is to pick up a cube and move it on a given trajectory.
At the end of the pre-stage, teams will be required to hand in a 3-page proposal and their code. Teams will be selected based on a combination of their score and the quality of the proposal.
Stage 1
The teams that passed the pre-stage will be granted access to the real robots and will be able to submit their code (instructions coming soon). The objective is to solve the same tasks as in the pre-stage, but now on the real robot.
At the end of this stage, participants will be required to hand in a 3-page report detailing the approaches used and their code (more information). Teams will be ranked based on the score achieved by their code, as long as the report passes an acceptance threshold.
Stage 2
In this stage, the cube is replaced by multiple, identical dice, which have to arranged in specific patterns.
At the end of this stage, participants will be required to hand in a 3-page report detailing the approaches used and their code (more information). Teams will be ranked based on the score achieved by their code, as long as the report passes an acceptance threshold.
Data Publication
When submitting jobs to the real robots, information like actions and observations as well as output of the user's application are recorded and stored (see documentation). During the challenge, participants can only access the data of their own submissions.
After the challenge, we may publish and use this data in anonymised form (i.e. excluding user-specific information/output) for research purposes.
By submitting jobs to the robots, users agree to this use of the generated data.
Important Dates
Schedule for 2021:
May 28th: Start of the Pre-Stage.: Submission deadline of the Pre-Stage (see Pre-Stage Submission Instructions).June 23thExtended until June 25th 14:00 UTCJune 29th, 08:00 UTC: Decisions on Pre-Stage and Access to Real-System is enabled for teams who successfully passed Pre-Stage.July 29thJuly 30th, 14:00 UTC: Submission deadline for final submission of Stage 1 (code).
23:59 UTC: Submission deadline for the report.
For more information see submission instructions.August 6th, 08:00 UTC: Winners of Stage 1 are announced and access to Stage 2 is enabled.- September 16th, 14:00 UTC: Submission deadline for final submission of Stage 2 (code).
23:59 UTC: Submission deadline for the report.
For more information see submission instructions.
Robotic Platform
An open-source version of the challenge robot, with identical actuators, almost identical kinematics, and identical software, is described in this paper and the corresponding site. The main difference with respect to the challenge platform is that the construction of the open-source version has been simplified considerably, such that researchers will be able to build it themselves.
Please note: For this challenge all the robotic platforms will be hosted at our institute, you do not need to build your own.
Some highlights of the design (of both versions):
Hardware Design
Each finger has 3 DoF and they share a workspace, permitting complex fine-manipulation.
This design has the following qualities:
- low weight, high torque
- 1 kHz torque control and sensing
- robustness to impacts due to transparency of transmission
Software Design
The key strengths of the software framework are:
- simple user interface in Python and C++ for control at up to 1 kHz
- safety checks to prevent the robot from breaking
- synchronized history of all inputs and outputs available and can be logged
Links & Literature
- Follow us on Twitter: @robo_challenge.
- Software Documentation
- If you are interested in getting access to the robots for custom research projects, see the information on the start page.
LITERATURE
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S. Bauer et al. „A Robot Cluster for Reproducible Research in Dexterous Manipulation“. arXiv preprint arXiv:2109.10957 (2021).
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M. Wüthrich, F. Widmaier, F. Grimminger, J. Akpo, S. Joshi, V. Agrawal, B. Hammoud, M. Khadiv, M. Bogdanovic, V. Berenz, J. Viereck, M. Naveau, L. Righetti, B. Schölkopf and S. Bauer. „TriFinger: An Open-Source Robot for Learning Dexterity“. In: Conference on Robot Learning (CoRL) (2020).
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D. Agudelo-Espana, A. Zadaianchuk, P. Wenk, A. Garg, J. Alpo, F. Grimminger, J. Viereck, M. Naveau, L. Righetti, G. Martius, A. Krause, B. Schölkopf, S. Bauer and M. Wüthrich. „A New Robotic Dataset for Transferable Dynamics Learning“. In: International Conference on on Robotics and Automation (ICRA) (2020).
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O. Ahmed, F. Träuble, A. Goyal, A. Neitz, M. Wüthrich, Y. Bengio, B. Schölkopf and S. Bauer. „CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning“. International Conference on Learning Representations (ICLR) (2021). International Conference on Learning Representations (ICLR) 2021
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N. Funk, C. Schaff, R. Madan, T. Yoneda, J. De Jesus, J. Watson, E. Gordon, F. Widmaier, S. Bauer, S. Srinivasa, T. Bhattacharjee, M. Walter und J. Peters. „Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation“. arxiv
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A. Allshire, M. Mittal, V. Lodaya, V. Makoviychuk, D. Makoviichuk, F. Widmaier, M. Wüthrich, S. Bauer, A. Handa, and A. Garg. "Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger." arXiv preprint arXiv:2108.09779 (2021).
Leaderboard
Stage 1
Final evaluation of stage 1 (30.07.2021)
# | Username | Score |
---|---|---|
1. | thriftysnipe | -11586 |
2. | decimalswift | -14714 |
3. | grumpyzebra | -29333 |
4. | dopeytacos | -35920 |
5. | worldlythrush | -44662 |
6. | solemnlollies | -45299 |
Videos of the "median runs" of the winning teams:
1. thriftysnipe
2. decimalswift
3. grumpyzebra
State of Monday, 26.07.2021
# | Username | Score |
---|---|---|
1. | grumpyzebra | -12296 |
2. | thriftysnipe | -23112 |
3. | dopeytacos | -34820 |
4. | worldlythrush | -43609 |
5. | solemnlollies | -44867 |
6. | decimalswift | -60000 |
State of Monday, 19.07.2021
# | Username | Score |
---|---|---|
1. | thriftysnipe | -31635 |
2. | solemnlollies | -31720 |
3. | grumpyzebra | -40854 |
4. | worldlythrush | -42313 |
State of Monday, 12.07.2021
# | Username | Score |
---|---|---|
1. | worldlythrush | -39416 |
2. | solemnlollies | -40177 |
3. | grumpyzebra | -60000 |
The listed score is the median over multiple goals. If the user code fails repeatedly on a given goal, that goal is assigned a score of -60000.
Participants who did not yet submit executable code are not included in the leaderboard.