In this challenge, you will have to develop an algorithm to control a multi-link arm robot interacting with a table, a shelf and a few objects. The robot is supposed to interact with the environment and learn in autonomous manner, i.e. no reward is provided from the environment to direct its learning. The robot has access to the state of its joint angle and to the output of a fixed camera seeing the table from above. By interacting with the environment, the robot should learn how to achieve different states of the environment: e.g. how to push objects around, how to bring them on top of the shelf and how to place them one on top of the other.
- August, 2020 - Round 1 starts.
- 15th October 2020 - Round 1 ends.
- November, 2020 Round 2 starts.
- End of January 2021, Round 2 ends.
- February, 2021 Final evaluations
The members of Top 3 teams will receive free registrations for the IEEE International Conference on Development and Learning (https://cdstc.gitlab.io/icdl-2020/)
Top 3 teams will be invited to co-author a paper - more details will be announced before Round 2 starts.