🏆 2025 BEHAVIOR Challenge - BEHAVIOR
Are you tired of coming home from school or work and having to cook food, clean the room or do your laundry. The forthcoming of AI was prophesied to automate all such mundane chores and spare us time to do the things we love. Yet, all that AI has done so far is to come for our jobs. Maybe you could change that. What if you can build an AI that takes over your chores instead of your job.
A team of engineers from Standford set out to do just that, to build a robot and to train a generalist AI model that can finally automate your household tasks. But, working with real robots can be complex and time consuming. So they have build a simulator that replicates household environments and spent 1000s of hours controlling (teleoperating) a virtual robot to do 50 different tasks in this environment. They compiled all that teleoperation data into a massive robotics dataset. Now, they need your help in training a single generalist AI model that can complete all these tasks!
Can you train a generalist AI robotics model using this dataset and make it successfully complete a subset of tasks?
If this feels daunting, don’t worry—there are generalist AI models for robotics that can help you get started. This is your chance to learn data science, work with real-world robotics data, and make a real impact.
If you don’t know what a generalist AI model is, then this excerpt from from the creators of Pi0 model **(**the chatGPT of robotics) might help:
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The promise of generalist robot policies
Today’s robots are narrow specialists. Programmed for repetitive motions in choreographed settings, repeatedly making the same weld in the same spot on an assembly line or dropping the same item into the same box. But even such simple behaviors require extensive manual engineering, and more complex behaviors in messy real-world environments such as homes are simply infeasible. AI could change that, allowing robots to learn and follow user instructions, so that programming a new behavior is as simple as telling the robot what you want done, and the robot can itself figure out how to adapt its behavior to its environment.
This requires data. Language models and other foundation models mine data from the web, utilizing a significant fraction of all available documents. There is no such treasure trove of robot data, so to enable a robot to learn a new skill, large amounts of data need to be collected with that particular robot and for that particular application.
If we could train a single generalist robot policy that can perform a wide range of different skills and control a wide range of different robots, we would overcome this challenge. Just as a person can learn a new skill quickly by drawing on a lifetime’s worth of experience, such a generalist robot policy could be specialized to new tasks with only modest amounts of data. In the same way that LLMs provide a foundation model for language, these generalist robot policies will provide a robot foundation model for physical intelligence.
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Watch Pi0 in action:
https://website.pi-asset.com/v2/upload/processed2xspeed_apartment_laundry_10min.mp4
https://website.pi-asset.com/v3/upload/processed_collage.mp4
Solve 50 full-length household tasks from our 1,000 activity collection, covering diverse activities like rearrangement, cooking, cleaning, and installation in the realistic BEHAVIOR-1K environment (evaluation). BEHAVIOR is a robotics challenge for everyday household tasks. It's a large-scale, human-grounded benchmark that tests a robot's capability in high-level reasoning, long-range locomotion, and dexterous bimanual manipulation in household scenarios.