Ep#115: Delta-0 (Δ₀): A New Chapter in Humanoid Intelligence

Delta Intelligence’s Δ₀ is a humanoid full-body foundation model, which can perform long-horizon, whole body loco-manipulation. They show a single, generalist policy which can control a 69-DoF humanoid to perform everyday tasks at nearly human speed — using whole-body human data for large-scale pretraining.Xiaojian Ma and Siyuan Huang tell us more about how they achieved this, and about the importance of jointly designing policy and controller. Delta uses a delta action space, for example, which makes it easy to provide human interventions without interrupting the whole body controller: a human operator can correct the robot seemlessly while it works.They show a wide range of impressive humanoid loco manipulation tasks using their generalist model.Learn more on Episode 115 of RoboPapers, with Michael Cho and Chris Paxton!Learn MoreBlog post: https://deltai.com/en/blog/delta-0TranscriptThis transcript has been edited for clarity and readability. Repetitions, false starts, and incidental screen-sharing chatter have been removed.Introducing Delta IntelligenceMichael Cho: Welcome to another episode of RoboPapers. Today we’re glad to have Xiaojian and Siyuan. Xiaojian is the CEO and Siyuan is the chief scientist of a new startup called Delta Intelligence. They’ve just released their model, Delta-0, along with a detailed technical blog post.We’re very glad to have both of you here to share your work. To start, could you each tell us a little about yourselves? Xiaojian, perhaps you can go first.Xiaojian Ma: Thanks, Michael and Chris, for the invitation. I’m Xiaojian, the CEO and founder of Delta Intelligence. Delta is dedicated to solving general intelligence for humanoid robots. We’re focusing on bipedal robots because we believe humanoids are the future and a general form of physical intelligence.We’re building foundation models that include both the brain—the large models—and the controller. We also work on hybrid force-position control for humanoids. Delta-0 is our first foundation model, showcasing the capabilities we currently have on Unitree G1 robots. We’re expanding beyond Unitree to other robot vendors in China and elsewhere, because we want our model to have cross-embodiment capabilities.Before founding Delta, I was a researcher in machine learning and robotics. I returned to China to join BIGAI as a research scientist in embodied AI. Before that, I was a PhD student at UCLA. During my PhD, I did research internships with teams at Google Robotics, NVIDIA Research, and Google DeepMind.My projects mostly involved building large multimodal models for reasoning and embodied decision-making. That’s the background I’m coming from.Siyuan Huang: Thank you for the invitation, Chris and Michael—two old friends. We’ve shared papers with you and my students several times, but this is the first time we’re discussing a blog post about Delta-0, our new foundation model.I’m the chief scientist of Delta. We released this blog at the end of last month, and it has prompted discussion about how to approach humanoid intelligence and build foundation models for whole-body loco-manipulation.We’re excited about the development of humanoid foundation models. This blog summarizes how we think we can build better models and address the coupled problems of the controller, hardware, and model.Watching the DemoSiyuan Huang: Let’s go over the demo first. We have two robots in an indoor environment. The first is doing what we call whole-body dexterous manipulation. The hardware is a Unitree G1 with two WUJI hands. The first task is putting a record onto a turntable.Michael Cho: And doing a dance, too. Nice.Siyuan Huang: Our expectation is that, in the future, we can have robots in our homes doing the same kinds of things people do: putting on a record, listening to music, doing a little dance, and taking a rest.They can also do everyday housework, such as making the bed, picking up a game controller, and arranging the bedding. These are long-horizon loco-manipulation tasks. They require whole-body coordination to finish everyday activities, such as picking up a toy from the ground and putting it on the bed.The robot can also interact with articulated objects, applying force to open and close doors. Here it’s opening the dishwasher and using its left hand for support so it can apply more force.Chris Paxton: That’s really cool. It was bracing itself against the fridge and pulling with the other hand.Xiaojian Ma: That’s right. It’s like using your