"在数字浪潮与智能革命奔涌的时代，青年人正是驾驭技术、定义未来的核心力量。广州，应该成为青 年科学家干事创业的首选地。"1月19日，在广州市两会现场，香港科技大学（广州）校长、讲座教授倪 明选接受了南方财经记者专访。他今年带来的提案聚焦广州如何打造青年科创雨林以及广州如何抢抓机 遇、建设具身智能产业创新高地。 南方财经记者谭砚文广州报道 2025年，"深圳-香港-广州"创新集群位列全球创新指数榜首，越来越多的青年人才和年轻企业成为科 创"千里马"。在倪明选看来，将人才与项目"流量"转化为发展"留量"的核心是从"成功后补贴"转向"启动 时关键投入"，打造一个择优、敢投、快投、能容错的友好型创业生态。 青年科创活力的迸发，也为广州布局前沿赛道筑牢了根基。2026年广州政府工作报告再提"具身智能产 业"。倪明选认为，广州可快速复用的产业底盘以及可闭环验证的场景生态，让广州不必从零开始构建 生态，就能快速完成"技术-产品-市场"的闭环验证。未来广州可进一步发挥优势，构建"广州研发、湾区 制造、全域示范"的具身智能产业集群。 打造青年科学家创业首选地 南方财经：你提出广州要将科创"流量"切实转化为发展"留量"。具体来看 ...

在数字基建的赛道上，枢纽效应持续释放。中国移动（600941）鲁南算力网络中心正式投产，辐射济宁、枣庄等四地市的算力版图，为新质生产力注入核 心动能；全市累计实施500万元以上工业新上和技改项目5543个，规上工业企业数字化深度转型率达到50%，实数融合效能全面释放。全市1.8万个5G基站 织就的通信网络，如同绵延舒展的"数字动脉"，持续为城市数字化迭代扩容。 产业集群的聚合效应愈发显著。珞石机器人作为链主企业，不仅成为首个挺进小米YU7焊装车间的国产工业机器人品牌，更吸引苏州明池、天达航科等20 余家上下游企业落户，推动核心零部件国产化率大幅提升。山东时代新能源基地的首批产品扬帆出海，山东时代新能源科技有限公司ISD经理郭孟超表 示："待整个项目全面建成后，济宁有望成为宁德时代（300750）北方产能最大、工艺最先进的储能电池与动力电池生产基地。"2025年，全市数字经济核 心产业营收突破700亿元，较2021年实现翻番，曲阜汽车电子、高新区数字终端等集群已成为省级标杆。 齐鲁晚报.齐鲁壹点孔茜 当鼓乐声与机械臂的运转韵律共振，光影秀中机器人精准勾勒出儒家文化符号。2026山东省机器人春节晚会的节目单上，济 ...

格隆汇1月21日｜A股市场机器人概念股走强，其中，奕帆传动20CM涨停，华瑞股份、三友医疗、天智 航-U涨超12%，方正电机、锋龙股份、铁流股份10CM涨停，科翔股份、华依科技涨超9%，中控技术、 信捷电气、华自科技涨超8%，宁波华翔、壶化股份、博实股份、本川智能涨超7%，浙江荣泰涨超5%。 ...

根据国家知识产权局最新公示清单，宇树分别于 1 月 6 日、20 日获批两项"人形机器人"外观专利，强调结构的简 洁化与模块化。 #模块化优势1：机器人商业化新思路。 通用平台+特定模块搭配，用户可以根据实际需求选择功能组件，而不必为不需要的功能付费。 宇树模块化外观专利获批，机器人商业化新思路| 国金具身cch团队 #模块化人形外观专利获批。 宇树模块化外观专利获批，机器人商业化新思路| 国金具身cch团队 #模块化人形外观专利获批。 【投资建议】 26年是人形机器人0-1兑现的重要节点，在这个阶段，龙头公司供应链、技术都会趋于收敛。 同时，全球将会迈入机器人"军备竞赛"，重点关注五大方向： （1）特斯拉链的收敛：围绕确定性和空间，重点关注：【拓普集团】【三花智控】【绿的谐波】【五洲新春】 【蓝思科技】【长盈精密】【浙江荣泰】【金沃股份】【恒勃股份】【领益智造】【均胜电子】【模塑科技】 【双环传动】、【恒立液压】（机械组覆盖）、【斯菱智驱、科森科技】（计算机组覆盖）等。 根据国家知识产权局最新公示清单，宇树分别于 1 月 6 日、20 日获批两项"人形机器人"外观专利，强调结构的简 洁化与模块化。 #模块化 ...

Summary of Key Points from the Conference Call Industry Overview - The focus is on the humanoid robot industry, specifically developments related to Weichuang Electric (688698.SS) and its supply chain involvement with U.S. humanoid robot manufacturers [1][1]. Company Insights - Weichuang Electric is a supplier of variable frequency drives, servo motors, and programmable logic controllers (PLCs) [1][1]. - The company has recently supplied various components such as rotary joint modules, coreless motors, frameless motors, and dexterous hand components to Chinese humanoid robot manufacturers [1][1]. - Weichuang Electric has successfully entered the supply chain of leading U.S. humanoid robot manufacturers by providing micro motors for dexterous hands [1][1]. Management's Key Points - Management expressed greater confidence in the mass production progress of U.S. humanoid robot manufacturers compared to Chinese clients, citing a more rigorous product development process [1][1]. - The capacity demand from the U.S. client is expected to increase tenfold by 2027, from 1,000 units per week in 2026 [1][1]. Strategic Partnerships - Weichuang Electric is collaborating with Rongtai Electric (603119.SS) to develop dexterous hand solutions for U.S. clients [4][4]. - Due to client requirements for all components to be produced outside of China, Weichuang announced plans to establish a joint venture with Rongtai in Thailand [5][5]. Production Requirements - The latest version of the humanoid robot requires each hand to have 22 degrees of freedom (DoF), totaling 44 micro motors for both hands [5][5]. - The U.S. client has requested that Weichuang prepare production capacity by the first half of 2026, aligning with recent industry research findings [5][5]. - Initial production targets are set to support the manufacturing of 1,000 humanoid robots per week, with potential demand increasing to 10,000 units per week by 2027 [5][5]. Valuation Insights - The target price for Hengli Hydraulic (601100.SS) is set at 135.0 CNY, based on a 52x expected P/E ratio for 2026, which is 2.0 standard deviations above its average P/E since 2021 [5][5]. - The target price for Railway Drive (688017.SS) is set at 233 CNY, based on a 233x expected P/E ratio for 2026, reflecting a stronger-than-expected profit recovery and increasing exposure to the humanoid robot business [8][8]. Risks - Key downside risks for Hengli Hydraulic include weak demand for excavator and non-excavator components, reduced profitability due to diminished economies of scale at the ball screw and Mexico plant, and lower-than-expected gross margin improvements from favorable product mix changes [6][6][7]. - For Railway Drive, risks include a slowdown in automation market growth, intensified competition from both domestic and international brands due to industry consolidation, rising raw material costs eroding gross margins, and lower-than-expected contributions from humanoid robots and other emerging applications [9][9].

数采方案也从仿真优先慢慢到UMI和更加拟人的方案演变，让数据能够规模化和好用，是各家公司一直探索 的。任务的差异化，也对数据的生产方式有一定的要求。 相比于传统机器人，具身领域的算法则更AI，从VLA、VLN到交互大模型，从强化学习到世界模型。基于 模仿学习和强化学习的方案，正在让模型变得更加泛化。 最近越来越多的同学开始准备具身方向的求职，算法、开发、仿真、强化、市场、产品等。不约而同的都再 问一句话，有没有好的求职指南？这个行业是怎么样的？ 这件事情，真的值得梳理一下。 2022年，当大多数人还没意识到"具身智能"即将爆发时，少数开拓者已经在悄悄地摸索着具身机器人的数 据、算法和推理。虽然没有达到那座山，但算法和硬件的高度一直在不断提升，场景也逐渐清晰。 本体层面的稳定性和实用性在陆续提升，从简单的双足、四足机器人，到更精美的人形和移动操作机器人。 场景一直决定着机器人的形态，各家零部件厂商也如雨后春笋般成长，强大的供应链让落地的成本不断下 降。 一个做算法的同学说，如果能把具身的上下游、开发流程、场景和商业化都过一遍就好了。开发的时候既知 道目的，又知道成本，游刃有余。不能管中窥豹，只见一斑。 一个想要 ...

Core Insights - The article presents a comprehensive review of Online Diffusion Policy Reinforcement Learning (DPRL), highlighting its potential to enhance robotic control through a unified algorithm taxonomy and benchmarking system [2][30]. Group 1: Challenges in Online DPRL - The integration of diffusion strategies with online RL faces three core challenges: incompatibility of training objectives, high computational costs and gradient instability, and insufficient generalization and robustness [4][5]. - The training objective conflict arises from the inherent incompatibility between the denoising training objectives of diffusion models and the policy optimization mechanisms of online RL [5]. - The computational and gradient issues stem from the multi-step backpropagation required for diffusion models, leading to high computational costs and potential gradient vanishing or explosion [5]. Group 2: Algorithm Classification Framework - The paper proposes a classification framework for Online DPRL algorithms, categorizing them into four main families based on their policy improvement mechanisms [7]. - Action-Gradient methods optimize policies directly through action gradients, avoiding the complexities of diffusion chain backpropagation, with algorithms like DIPO and DDiffPG [9]. - Q-Weighting methods modulate diffusion loss using Q-value weights to guide policies towards high-reward areas, represented by algorithms such as QVPO and DPMD [10]. - Proximity-Based methods approximate the calculation of policy probability densities, enhancing performance in large-scale parallel environments, exemplified by algorithms like GenPO [11]. - BPTT-Based methods utilize end-to-end backpropagation through the entire diffusion process, with algorithms like DACER, but face scalability issues as diffusion steps increase [12]. Group 3: Empirical Analysis and Benchmarking - A unified benchmarking system was established on the NVIDIA Isaac Lab platform, covering 12 robotic tasks to systematically evaluate algorithm performance across five key dimensions [13][15]. - The analysis revealed that GenPO ranked first in 6 out of 12 tasks, while DIPO performed best in offline strategies with an average ranking of 3.58 [15]. - Performance in parallel environments showed that GenPO and PPO significantly improved in larger scales, while DIPO demonstrated robustness across varying parallelization scales [18]. Group 4: Performance and Generalization - The study assessed the impact of diffusion step expansion on performance and latency, finding that Action-Gradient and Q-Weighting methods improved with increased steps, while BPTT methods faced performance declines beyond 20 steps [21]. - Cross-robot generalization tests indicated that offline strategies like DIPO and QVPO exhibited stronger transfer robustness compared to online strategies, which struggled with significant hardware differences [23]. - The robustness of algorithms in out-of-distribution environments was evaluated, with GenPO showing excellent performance in certain scenarios but also a risk of overfitting to source environments [27]. Group 5: Conclusions and Future Directions - The review establishes a theoretical framework for Online DPRL, revealing trade-offs between sample efficiency and scalability, as well as performance and generalization [30]. - Recommendations for algorithm selection include prioritizing GenPO for large-scale simulations, DIPO for resource-constrained scenarios, and Action-Gradient or Q-Weighting methods for high-precision tasks [31]. - Future research directions include integrating safety constraints, exploring multi-agent DPRL, and developing hierarchical RL architectures to enhance exploration efficiency [31].

Core Viewpoint - The article discusses the development of an autonomous robotic system for intraocular surgery, which significantly enhances precision and safety in retinal injections, addressing a critical challenge in ophthalmic surgery [2][3][10]. Group 1: Technological Breakthroughs - The research team from the Chinese Academy of Sciences has developed the ARISE system, achieving a 100% success rate in injections across various experimental models, with an average positioning error reduced by 79.87% compared to manual surgery [2][10]. - The system utilizes a comprehensive navigation module that integrates multiple imaging modalities, creating a dynamic 3D map with a lateral resolution of 4.7 micrometers and a depth resolution of 6 micrometers, achieving a 99.08% accuracy in reproducing the actual retinal depth [5][10]. - A multi-constraint objective optimization method was developed to plan the robot's trajectory, ensuring safety through a hybrid control system that combines force, position, and imaging [6][10]. Group 2: Clinical Implications - The ARISE system demonstrates a significant performance advantage, with an average positioning error of 11.71 micrometers, compared to 25.80 micrometers for remote-controlled robots and 58.17 micrometers for human surgeons [10]. - The system maintains a 100% success rate in challenging procedures, such as branch retinal vein injections, where human success rates decline due to the smaller vessel diameter [10]. - The autonomous robot completes the injection process in an average of 79.16 seconds, providing consistent performance without fatigue or stress affecting its operation [10]. Group 3: Future Prospects - The research indicates a new technological pathway for the autonomy of intraocular surgeries, potentially advancing ophthalmic treatments, especially in remote medical settings and extreme environments [10]. - The ARISE system represents a significant step towards the intelligent and precise evolution of ophthalmic surgery, reducing reliance on scarce medical resources and shortening the learning curve for surgeons [10].

Core Insights - Redwire Corporation is transitioning from a space manufacturing firm to a critical infrastructure vendor, with stock trading in the $11-$12 range and showing bullish signals through insider buying [2][6][7] - The company reported a revenue of $103.4 million in Q3 2025, a 50.7% year-over-year increase, and has a backlog of $355.6 million, indicating sustained revenue growth [6] - Ondas Holdings is experiencing rapid growth with a 582% increase in revenue to $10.1 million in Q3 2025, driven by demand in the defense sector [10][12] - Nauticus Robotics is undergoing a turnaround, recently achieving deep-sea testing success, which has opened commercial opportunities with major energy companies [14][16] Company Summaries Redwire Corporation - Redwire has pivoted to become a hybrid defense player, acquiring Edge Autonomy to supply unmanned aerial systems to defense clients [7] - The company's space division continues to thrive with Roll-Out Solar Arrays (ROSA), essential for the International Space Station [8] - Insider buying from executives suggests confidence in the stock's undervaluation [2][5] Ondas Holdings - Ondas specializes in autonomous drone technology and has seen significant interest from institutional traders, indicated by a 142% spike in unusual call options activity [9] - The Iron Drone system has gained traction due to rising demand in conflict zones, expanding Ondas's market reach [12] - The company is positioned for high-velocity growth, despite potential stock volatility [12] Nauticus Robotics - Nauticus is focused on replacing traditional offshore energy ships with autonomous robots, recently achieving a critical milestone with its Aquanaut robot [13][14] - The company has restructured its debt and formed a partnership with Forum Energy Technologies to enhance its manufacturing capabilities [16] - The stock is viewed as a high-risk, high-reward investment opportunity, with potential for significant price appreciation [16] Industry Trends - There is a notable capital rotation towards frontier robotics, emphasizing the value of tangible industrial technology over consumer gadgets [17] - Companies like Redwire, Ondas, and Nauticus are building essential infrastructure for the next generation of the global economy, focusing on sectors with high barriers to entry [17][18] - The frontier robotics sector is showing signs of maturity, with bullish data signals indicating potential for growth in 2026 [18]

Core Insights - Serve Robotics has agreed to acquire Diligent Robotics, which specializes in creating robot assistants for the healthcare sector [1] Company Summary - Serve Robotics is expanding its portfolio by acquiring Diligent Robotics, indicating a strategic move to enhance its capabilities in the healthcare industry [1] - Diligent Robotics focuses on developing robotic solutions aimed at assisting healthcare professionals, which aligns with the growing demand for automation in healthcare settings [1]