Core Insights - The article emphasizes the acceleration of innovation in artificial intelligence and digital technologies, focusing on breakthroughs in foundational theories and core technologies, as well as enhancing the efficient supply of computing power, algorithms, and data [1]. Group 1: Technological Advancements - A significant achievement was made when a bionic dual-arm robot successfully completed the autonomous transfer of samples, showcasing its ability to perceive, reason, and execute tasks like a human [2]. - The development process involved enhancing machine vision for precise identification and creating a rapid detection instrument for pharmaceuticals, addressing the challenge of integrating these independent systems [2][3]. - The team overcame the challenge of combining a flexible robotic body with a precise analytical instrument brain, introducing a large model as the intelligent core to achieve full-process autonomy [2][3]. Group 2: Design and Control Innovations - The first technical challenge addressed was the "bionic-driven integrated lightweight design," which involved creating a modular solution for single-joint integrated drive, sensing, and control to reduce weight and enhance response speed while achieving millimeter-level grasping precision [3]. - The next challenge was to endow the robot's "brain" with intelligent decision-making capabilities, leading to the development of a hierarchical decision control strategy driven by large models, creating a closed loop of understanding, planning, and control [3]. - An innovative "physical feedback learning" mechanism was established to record collision points and key parameters, converting these "failure experiences" into training data to continuously refine the large model's understanding and improve success rates [3]. Group 3: Future Goals - The goals for the upcoming "14th Five-Year Plan" include continuous breakthroughs in bionic integrated structures, the introduction of soft materials, and the coupling design of rigid and flexible components [3]. - There is a focus on deepening the integration of large models with embodied intelligence, tackling long-sequence task planning and multi-modal real-time decision-making capabilities [3]. - The aim is to construct an intelligent system demonstration that integrates "large models, bionic entities, and precision instruments," providing a universal solution applicable to laboratory automation and precision operations [3]. Group 4: Embodied Intelligence - Embodied intelligence is defined as enabling robots to perceive, think, and act in the physical world like humans, requiring a deep integration of bionic structural design and large model decision-making capabilities [4]. - The article highlights the necessity of simulating the complex coordination of human skeletal and muscular systems through breakthroughs in materials science and topology optimization [4]. - A cross-disciplinary team has been formed to address the challenges of understanding physical laws through real-world interactions, pushing the boundaries of embodied intelligence into broader application scenarios [4].

"仿生驱动的一体化轻量化设计"是我们首先要攻克的技术难题。实验室空间有限，而且需要长时间精密 操作，传统机械臂因自重大、惯性强而难以胜任。我们借鉴人体肌肉—骨骼协同机制构建模型，提出单 关节集成驱动、传感与控制的模块化方案。同时优化材料分布，使整机重量大幅减轻，在提升响应速度 的同时，实现毫米级的抓取精度。 加快人工智能等数智技术创新，突破基础理论和核心技术，强化算力、算法、数据等高效供给。 ——摘自"十五五"规划建议 今年的一次实验，让实验室所有人都屏息凝视：当玻璃瓶被仿生双臂机器人稳稳放置在医药光谱检测仪 上时，团队成员长舒了一口气。仿生双臂机器人首次自主完成样本转移，这个看似简单的任务，却要求 它像人一样感知、推理、执行。具体来说，需要通过多模态系统识别目标，依靠大模型规划路径，用仿 生灵巧手精准抓取，实时协调双臂避免碰撞。这一刻，"大模型赋能具身智能"从概念变为现实，机器人 具备了自主决策能力。 回顾研发过程，团队先是深耕机器视觉，让工业设备"看得准"，后又自主研发医药光谱快速检测仪器， 实现"测得精"。然而，这些系统相互独立，如何将它们串联起来成为亟须解决的难题。近年来，我们攻 克了将灵活的"机器人 ...