“As artificial intelligence gains new capabilities, it becomes important to evaluate it on real-world tasks. While software such as ChatGPT has recently revolutionized certain areas of AI, athletic intelligence seems to still be elusive in the AI community. To have better robots in the future which can perform a wide variety of dynamic tasks in uncertain environments, the physical or athletic intelligence of robots must be improved. However, this is quite challenging. In particular, the fields of robotics and reinforcement learning (RL) lack standardized benchmarking tasks on real hardware. To facilitate reproducibility and stimulate algorithmic advancements, the 3rd AI Olympics competition is being proposed to be held at ICRA 2025 in Atlanta following the inaugural run at IJCAI 2023 in Macau (https://ijcai-23.dfkibremen. de/competitions/ai_olympics/, see https://www.youtube.com/watch?v=eYDH1v1FqF8 for a video summary), based on the RealAIGym project and 2nd edition of this competition at IROS 2024 in Abu Dhabi (https://ai-olympics.dfki-bremen.de/). While the inaugural run of this competition focussed on comparing the performance of various learning and control methods on the real acrobot/pendubot systems, the second edition at IROS focussed not only on achieving the best scores but also on achieving robustness to disturbances during the execution.
At ICRA 2025, the focus of the challenge would be to develop a global policy that can solve the swing up problem from any configuration in the state space thus improving the controllers in the 3rd edition of this challenge. This will be tested by randomly disturbing the system with very large (compared to IROS 2024) external disturbances while it performs the swingup task. The challenge will involve two stages: simulation and realrobot experiments where teams (and their agents) can compete to get the highest score to win some cool prizes! We invite people from all communities (AI/ML/RL, Optimal Control, Heuristics, etc.) to participate in this competition on a set of standardized dynamic tasks on well-known prototypical systems using standardized hardware.”
