open-source

Menlo Research’s open-source project, Asimov, moves from GitHub repository to physical hardware with a bipedal kit designed for rapid iteration and "Processor-in-the-Loop" development.

NVIDIA researchers have revealed EgoScale, a framework that leverages a massive 20,854-hour egocentric human dataset to train robots in complex, fine-grained manipulation with minimal robot-in-the-loop data.

NVIDIA has released SONIC, a generalist humanoid controller trained on 100 million frames of motion data, aiming to replace manual reward engineering with a scalable "System 1" foundation for whole-body movement.

NVIDIA GEAR Lab has released DreamDojo, an open-source world model pretrained on a massive 44,000-hour dataset of human egocentric videos. By using "latent actions" to bridge the gap between human and robot movement, the model achieves zero-shot generalization and real-time controllability for teleoperation and planning.

RoboParty has released the full-stack designs and software for its first bipedal humanoid, signaling a new wave of "reproducible" open-source robotics that seeks to avoid the capital-intensive pitfalls of its predecessors.