🔥 High-Value Papers (Rating > 3.0, Recommended to Download the Original for In-Depth Study) 1. Learning Adaptive Neural Teleoperation for Humanoid Robots: From Inverse Kinematics to End-to-End Control Abstract: Virtual reality (VR) teleoperation has become a promising method for controlling humanoid robots in complex manipulation tasks. However, traditional teleoperation systems rely on inverse kinematics (IK) … Read more
The Sports AI Agent is reconstructing the training logic of competitive sports and the management paradigm of public health with its core capabilities of “autonomous decision-making + cross-domain collaboration.” It is not merely an upgrade of traditional AI tools, but a “digital athlete partner” that deeply integrates sports science, machine learning, and intelligent hardware, achieving … Read more
Click to join the discussion group→👥 Discuss with 1000+ embodied intelligence researchersEntrepreneurship × RL × VLA Open Source Project Collection: Yushu | VLA | Reinforcement Learning Control | RL Framework Practice | Unitree RL_Gym Core Ideas and Innovations 💬 Editor’s Perspective GentleHumanoid allows the robot’s upper body to be compliant, enabling it to move along … Read more
Selected robotics papers from arXiv! 👏👏👏 #Robotics ForeRobo: Unlocking Infinite Simulation Data for 3D Goal-Driven Robotic Manipulation Date: November 6, 2025 Authors: Dexin Wang, Faliang Chang, Chunsheng Liu Link: http://arxiv.org/abs/2511.04381v1Efficiently utilizing simulation to acquire advanced manipulation skills is both challenging and highly important. We introduce ForeRobo, a generative robotic agent that autonomously acquires manipulation skills … Read more
Your question is very critical! Indeed, Huawei’s Ascend series chips are based on NPU (Neural Processing Unit) architecture, which is fundamentally different from general-purpose accelerators like NVIDIA GPUs. However, it does not mean that it cannot perform high-end training; rather, there are differences in technical routes, ecosystem maturity, and absolute computing power. The following is … Read more
Based on the Chip Learning framework proposed by Academician Chen Yunji and the technical positioning of Zhonghao Xinying, combined with an analysis of the current industry situation, Zhonghao Xinying has the potential to explore chip learning, but it is difficult to achieve a breakthrough in the entire process in the short term. The following is … Read more
🤖 Self-Evolution: How LLM Achieves Breakthroughs in General Domain Capabilities through “Three Kingdoms Kill”? — In-Depth Analysis of Multi-Agent Evolve (MAE) 🌟 Introduction: Breaking Through the “Data Drought” and “Reward Wall” in LLM Training Large Language Models (LLMs) have shown tremendous potential in reasoning tasks, but their capability enhancement is often constrained by two core … Read more
Selected robotics papers from arXiv! 👏👏👏 #Robotics RoboOS-NeXT: A Unified Memory-Based Framework for Lifelong, Scalable, and Robust Multi-Robot Collaboration Date: October 30, 2025 Authors: Huajie Tan, Cheng Chi, Xiansheng Chen, Yuheng Ji, Zhongxia Zhao, Xiaoshuai Hao, Yaoxu Lyu, Mingyu Cao, Junkai Zhao, Huaihai Lyu, Enshen Zhou, Ning Chen, Yankai Fu, Cheng Peng, Wei Guo, Dong … Read more
1. IBM Releases Granite 4.0 Nano Series Small AI Models IBM has launched four Granite 4.0 Nano models with parameter scales ranging from 3.5 million to 1.5 billion, capable of running on standard laptops or even locally in browsers. These models are open-sourced under the Apache 2.0 license for commercial and research use, certified with … Read more
Deep Reasons Behind the Slow Progress of AI Humanoid Robot Training Technology and Real-World Applications The Dual Challenge of Embodied Intelligence and Commercial Viability Currently, the world’s most advanced AI robotics companies have made breakthrough progress in training humanoid robot AI. The application of large language models (LLMs) and visual language models (VLMs) has significantly … Read more