UUnitree Latest coverage

LEGS: Fine-Tuning Teleop-Free VLAs for Humanoid Loco-manipulation in an Embodied Gaussian Splatting World

This research presents LEGS, a hybrid simulator that combines a mesh foreground with a photorealistic 3D Gaussian Splatting background to train vision-language-action (VLA) policies for humanoid loco-manipulation without human teleoperation. The method uses a procedural motion-primitive generator to synthesize labeled demonstrations and a two-stage color calibration to align renders with the deployment camera. Policies trained on LEGS data match or exceed those trained on human teleoperation demos and outperform mesh-only baselines. The approach enables cost-effective re-rendering of demonstrations for new scenes and objects.

ASENA: Self-evolving Agents for Embodied Navigation

This paper introduces ASENA, an embodied agent system that enables general-purpose coding agents to program humanoid navigation, manipulation, and interaction. ASENA-VLN, a 4B monocular navigation policy, achieves state-of-the-art success rates on R2R and RxR benchmarks. Integration with coding agents improves success rates and reduces execution time, while persistent workspace evolution enhances performance through simulator feedback.

PartiGen: Part-Aware Representations for Language-Conditioned Humanoid Motion Generation

This paper introduces PartiGen, a part-aware latent diffusion framework that integrates anatomical structure into whole-body motion representations.

Long-WAM: Scaling the Context of World-Action Models

This research presents Long-WAM, a model-system framework that scales the context of causal world-action models under real-time control constraints. By using autoregressive pretraining, the model improves task success rates on benchmarks like RoboCasa GR-1 and LIBERO-Long. It also supports real-time deployment on hardware platforms, enabling dynamic and long-horizon manipulation tasks.

2026 Robot Industry 'Brain' Track Review: Two Paths of Unitree and Xian Gong Intelligence

In 2026, the robot industry shifted from hardware competition to a contest of 'brain' capabilities. The article analyzed the technical stack of 'robot brains,' including perception, cognition, planning, and control layers, and discussed the importance of data loops. The article focused on two companies, Unitree Technology and Xian Gong Intelligence, representing the 'body-centric' and 'brain-centric' approaches respectively, exploring their deployment strategies and data accumulation methods in real-world scenarios.

NVIDIA releases G1-Factory-GR00T-1.7 policy for Unitree G1 humanoid

NVIDIA released G1-Factory-GR00T-1.7, a GR00T N1.7 vision-language-action policy fine-tuned on nine simulation tasks for the Unitree G1 humanoid robot. The model takes head-camera images and joint states to predict whole-body actions and serves as a baseline for reinforcement learning post-training. It is available under the NVIDIA Open Model License for commercial and non-commercial use, with evaluation results reported only in simulation.

Can Embodied Intelligence Be Trusted? Sergey Levine Points the Way

At the 2026 World Robotics Conference, Sergey Levine pointed out that the robotics industry is undergoing a shift from controlling the body to developing decision-making capabilities. He emphasized that robots need to combine prior knowledge with real-world experience to achieve true intelligence. Although robots are still in the foundational technology stage, through data flywheels and scaling, they may eventually enable broader applications.

GPT-6 Astra Connects to Unitree G1, Cleans the Kitchen

The Stanford team's HomeBody project demonstrates how GPT-6 Astra controls the Unitree G1 robot to complete kitchen cleaning tasks through a three-step process: spatial exploration, digital twin simulation, and task execution. The system uses pre-trained models and a skill library to perform complex operations in new environments without additional training.

Unitree@UnitreeRobotics· 09:01SignalEditorial score6868

Unitree has fully open-sourced its UnifoLM-WLA-1.0 embodied foundation model, achieving new state-of-the-art results across multiple benchmarks. The model supports cross-task and cross-end-effector generalization, enabling whole-body coordination for both desktop and mobile manipulation.

Unitree@UnitreeRobotics· 13:10SignalEditorial score7272

Unitree says it supports BitRobot in open-sourcing HIW-500, a humanoid teleoperation dataset collected across 12 real homes in Southeast Asia. The quoted announcement reports 500+ hours, 23K+ episodes, 10+ TB and more than 10 household tasks. The post does not specify the time basis or license, or link to a downloadable artifact.