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Edward Johns

@Ed__Johns • 3,840 subscribers

Associate Professor and Director of the Robot Learning Lab at Imperial College London.

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At every robotics conference I go to, I am guaranteed that a dancing circle of assorted robots will spontaneously emerge at some point… #ICRA2023

At every robotics conference I go to, I am guaranteed that a dancing circle of assorted robots will spontaneously emerge at some point… #ICRA2023

39,301 views

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I'm very excited to finally announce one of the most ambitious projects we've worked on — which makes the front cover of Science Robotics today: ☀️ Learning a Thousand Tasks in a Day ⭐️ Everyday tasks — like those below — can now be learned from a single demonstration each...

I'm very excited to finally announce one of the most ambitious projects we've worked on — which makes the front cover of Science Robotics today: ☀️ Learning a Thousand Tasks in a Day ⭐️ Everyday tasks — like those below — can now be learned from a single demonstration each...

109,298 views • 7 months ago

This is a single uncut video, showing a robot learning several tasks instantly, after just one demonstration each ... This is possible because we've now been able to achieve in-context learning for everyday robotics tasks, and I'm very excited to announce our latest paper: 🎆 Instant Policy: In-Context Imitation Learning via Graph Diffusion 🎆 (1/6) 🧵👇

This is a single uncut video, showing a robot learning several tasks instantly, after just one demonstration each ... This is possible because we've now been able to achieve in-context learning for everyday robotics tasks, and I'm very excited to announce our latest paper: 🎆 Instant Policy: In-Context Imitation Learning via Graph Diffusion 🎆 (1/6) 🧵👇

74,663 views • 1 year ago

I have Post-Doc, PhD, and Research Assistant positions available, for a new project working with me on dexterous robot learning! Come and join me, my team, and our robots, at Imperial College London! 🤖🧑‍💻🇬🇧💂🤖 See for more info. Please share/retweet!

I have Post-Doc, PhD, and Research Assistant positions available, for a new project working with me on dexterous robot learning! Come and join me, my team, and our robots, at Imperial College London! 🤖🧑‍💻🇬🇧💂🤖 See for more info. Please share/retweet!

25,049 views • 1 year ago

Very excited to announce: Keypoint Action Tokens! We found that LLMs can be repurposed as "imitation learning engines" for robots, by representing both observations & actions as 3D keypoints, and feeding into an LLM for in-context learning. See: More 👇

Very excited to announce: Keypoint Action Tokens! We found that LLMs can be repurposed as "imitation learning engines" for robots, by representing both observations & actions as 3D keypoints, and feeding into an LLM for in-context learning. See: More 👇

32,569 views • 2 years ago

At #ICRA2025, I'm about to present: "R+X: Retrieval and Execution from Everyday Human Videos". By using a VLM for retrieval and in-context IL for execution, robots can now learn from just videos of humans! Led by George Papagiannis and Norman Di Palo. See:

At #ICRA2025, I'm about to present: "R+X: Retrieval and Execution from Everyday Human Videos". By using a VLM for retrieval and in-context IL for execution, robots can now learn from just videos of humans! Led by George Papagiannis and Norman Di Palo. See:

11,962 views • 1 year ago

Here's another video of emergent behaviour from Instant Policy, which we released yesterday. You will see that when a demo is provided only for Box 1, the robot fails to generalise well to Boxes 2 and 3. But then we add in a demo for Box 4, and the robot can now successfully generalise to Boxes 2 and 3. One of the exciting features of Instant Policy is that, since we encode everything in a graph neural network, we can keep on adding as many demonstrations as we like until we have covered the required task diversity.

Here's another video of emergent behaviour from Instant Policy, which we released yesterday. You will see that when a demo is provided only for Box 1, the robot fails to generalise well to Boxes 2 and 3. But then we add in a demo for Box 4, and the robot can now successfully generalise to Boxes 2 and 3. One of the exciting features of Instant Policy is that, since we encode everything in a graph neural network, we can keep on adding as many demonstrations as we like until we have covered the required task diversity.

12,418 views • 1 year ago

R+X was accepted at ICRA 2025! Robots can now do in-context imitation learning, just by observing humans going about their daily lives... No more need to *label* and *train* - just *RETRIEVE* and *EXECUTE*! 🧵👇 (1/5)

R+X was accepted at ICRA 2025! Robots can now do in-context imitation learning, just by observing humans going about their daily lives... No more need to label and train - just RETRIEVE and EXECUTE! 🧵👇 (1/5)

10,209 views • 1 year ago

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