Teamwork makes the dream work. To test multi-robot collaboration with Gemini Robotics 2, we challenged our Apollo and Duo robots to tidy up a messy garage. The high-level reasoning model breaks down what to do, where to go, and identifies the exact moment to hand over control ↓

To be truly useful, a robot needs the dexterity that humans take for granted. But asking AI models to coordinate these motions is incredibly complicated. In this demo, we pushed Apollo 2 to master fine motor skills and complete tricky kitchen chores ↓

This is how Gemini Robotics 2 helps @Apptronik’s Apollo 2 use whole body intelligence to pack for a sports game ↓

The exact handoff moment is where these demos usually wobble

The handoff point is where multi-robot systems get interesting. Is that decision based only on task semantics, or does the model also use live confidence, reachability, and robot health signals before transferring control?

The handoff moment is where the coordination gets interesting.

whole body coordination for packing is a good stress test, most manipulation work quietly assumes a static base

apollo and duo hand off garage tasks without a human mid loop

the model's playing foreman here - deciding which robot does what and when to swap, not a person directing traffic. one robot running a script is normal now, two working out who goes next isn't.

Which robot gets blamed when they both decide the other one was supposed to pick it up?

The handoff logic is the interesting part here. I’d love to see how it handles a blocked path or a missing tool without breaking the whole plan.

The handoff moment is the real test here—not just two robots following scripts, but a model deciding when control should move between bodies. I’d score coordination failures and recovery time, too.

the handoff moment is the hard part, most demos skip straight to the pretty grab