This robot is being controlled by someone 5,500 miles away.
This is a demo of our teleoperation stack at @Adamorobotics. The robot is in our London office. The operator is in San Francisco.
The bottleneck in robotics has shifted from R&D to deployment. Robots still can't handle every edge case. When autonomy fails, you need a human in the loop, fast.
We've built the fastest teleoperation stack on the planet for remote human control of any robot, anywhere in the world.
This is what makes real-world deployment possible today.
Every day, we power thousands of interventions for humanoid and autonomous vehicles, and we're only just getting started.
You can now try it yourself for free, at https://t.co/HXNiOT3ZhN
I’ve been capturing 3D human motion for 30 years and today is maybe the biggest day in that history. We are presenting MAMMA at CVPR (oral session 2A). MAMMA is a markerless multi-camera system that has accuracy similar to marker-based systems.
Excited to share E3VS-Bench, a benchmark for Embodied 3D Visual Search!
Many existing visual search benchmarks can be solved from a limited set of viewpoints or through planar navigation alone.
However, real-world visual search often requires richer viewpoint control: looking up or down, moving higher or lower, and inspecting objects from specific viewing angles to reveal information hidden by occlusions or object geometry.
To study this challenge, we introduce E3VS-Bench, a benchmark for viewpoint-dependent active perception in photorealistic 3D environments.
🔹 2,014 visual search episodes
🔹 Built on 99 real-world 3DGS scenes
🔹 Full 5-DoF viewpoint control
🔹 Human and frontier VLM evaluation
Our results reveal a substantial gap between humans and current models, highlighting the difficulty of active perception in 3D environments.
🌍 Project Page: https://t.co/9opDeSpvdV
📄 Paper: https://t.co/S6RbcuObs7
💻 Code & Dataset: https://t.co/JHdHQlgKWv