Pollen Robotics and Hugging Face launched Microduck, a 25 cm open-source bipedal robot priced at $399, available for pre-order in four colorways with shipping before Christmas 2026. The robot features…
Apptronik, a human-centered robotics company developing AI-powered robots, is hiring a Senior Reinforcement Learning Engineer for its Sunnyvale, CA office to implement and deploy state-of-the-art RL a…
Apptronik, a human-centered robotics company developing AI-powered robots, is hiring a Lead Software Engineer for Dexterous Manipulation in Sunnyvale, CA, to lead the development of learning-based dex…
Researchers propose IADD-TR, a framework that decouples environment dynamics into action-intervention and action-free stages to reduce policy-induced data bias in model-based reinforcement learning. E…
Google DeepMind released Gemini Robotics 2, a single model that unifies locomotion and manipulation for humanoid robots, eliminating the previous split between walking and arm-control systems. The mod…
Master's students pursuing RL research should focus on embodied AI, particularly Vision-Language-Action (VLA) models, as the strongest bet, according to an analysis of current trends. Brain-computer i…
A new analysis of physical AI simulation finds that high-fidelity environments like NVIDIA Isaac Gym and MuJoCo are viable for training LLM agents that interact with the physical world, but a hybrid a…
Unitree Robotics received regulatory approval on July 3 for a $619 million IPO on Shanghai's STAR Market, becoming the first humanoid robot company to go public on China's domestic A-share market. The…
Researchers introduced SPEAR, a Python library that programmatically controls Unreal Engine applications for photorealistic embodied AI research. It offers over 14,000 programmable functions, renders …
Lucky Robots launched Lucky Engine, the first game engine purpose-built for robotics, enabling infinite data generation for robotic AI training. The engine provides physically accurate simulation with…
SimTooReal, a platform for robotics teams, now enables live telemetry and failure diagnosis for training runs in Isaac Lab, MuJoCo, Gazebo, and LeRobot with a single command. The tool wraps existing t…
Researchers found that LLM-generated reward functions for sparse reinforcement learning tasks fail in predictable ways, including reward flooding and API misunderstandings. A diagnostic-driven refinem…
Researchers developed a personalized observation normalization (PON) method to address heterogeneity in federated reinforcement learning, where differing state-transition dynamics cause non-identical …