Great work - Robot/object/contact co-tracking and curriculum via virtual object controllers are really good ideas. We will see similar ideas for humanoid whole-body manipulation and loco-manipulation very soon!

thank you Michael Black ! The name DexMachina came from Deus ex machina (“god from the machine"): when a seemingly unsolvable problem is conveniently solved by an external force - like how our algorithm moves an object by itself before the policy gradually learns to take over

Single view reconstruction for cluttered scenes!

How can we move beyond static-arm lab setups and learn robot policies in our messy homes? We introduce HoMeR, an imitation learning agent for in-the-wild mobile manipulation. 🧵1/8

I'm giving a spotlight talk 10AM tomorrow, Room 213 at the agents-in-interactions workshop at #CVPR. Poster session is 11:45-12:15 at ExHall D #182-#201. Come say hi! Workshop schedule: agents-in-interactions.github.io

Normally, changing robot policy behavior means changing its weights or relying on a goal-conditioned policy. What if there was another way? Check out DynaGuide, a novel policy steering approach that works on any pretrained diffusion policy. dynaguide.github.io 🧵

I’m a big fan of this line of work from Columbia (also check out PhysTwin by Hanxiao Jiang: jianghanxiao.github.io/phystwin-web/) they really make real2sim work for the very challenging deformable objects, And show it’s useful for real robot manipulation. So far it seems a bit limited to

Probably the first and only public video from Skild AI: seeing Frankas, UR5s, humanoid arms - all bimanual robotiq 2f85 grippers?