The challenge is divided into two stages:
- Pre-Stage: The pre-stage of the challenge serves as an open qualification round where everyone can participate. This stage is done completely in simulation, so no access to the robots is needed.
- Robot Stage: The best teams of the pre-stage are admitted to the real-robot stage where the same tasks have to be solved on the real robots. For this the teams will get remote access to our TriFinger robot cluster.
The goal of this year’s challenge is to solve dexterous manipulation tasks with offline reinforcement learning (RL) or imitation learning. The participants are provided with datasets containing dozens of hours of robotic data and can evaluate their policies locally in simulation (pre-stage) or remotely on a cluster of real TriFinger robots (robot stage).
There are two tasks of different difficulty:
- Push a cube to a target location on the ground.
- Lift a cube to match a target pose (position and orientation) in the air.
In the pre-stage, participants only get access to datasets with data collected in simulation and also evaluate their policies only in simulation. In the real robot stage, participants get access to dataset containing data collected on 6 robots.
For more detailed information on how to participate, please see the software documentation.