大家还记得去年 靠 自制兽装控制器 火遍 全网 的重庆交大学生黄彦钧吗？ 没错，就是那个实现了 生物仿生学眨眼 、配备 夜视仪 和 图像识别算法 ，还在头套里装了 换气系统 的 " 硬核玩 家 "， 冲上了热搜。 这回，他又整活了。 最新作品是 一套 真· " 钢铁侠 " 战甲！ 央视亲自转发，外网直接炸锅了。 这套战甲 全身能自动开合，迅速变形贴合身体， 例 如 肩周全自由度， 手臂 可自动闭合。 有趣的是， 机甲还接入了AI语音对话， 和贾维斯助理对话起来真的超酷好么！ 还配有 机甲 信息终端，看信息就和看手表一样简单。 最让网友惊讶的是，IMU体感触发系统可以根据特定动作实现 手 臂 电磁冷发射架的启动， 能发射"导弹"，根据展示需要，加装烟雾、激光束等武器道具！ 更厉害的是， 战甲 中的 助力外骨骼还可以提供额外动力，增强人体极限！ 网友直呼：" 现实版钢铁侠照进现实 。 " " 这不 军迷 减速带吗！ " 这位 00 后此前还研发过 外骨骼辅助行走机器人 并获得专利，参与过 清华大学脑机接口领域实验室 项目 ，甚至以 " 战术装备研发人员 " 的头衔登上央视军事 频道。 从 " 拆家电少年 " 到 ...

Core Viewpoint - The article discusses the development of Kinethread, a full-body haptic exoskeleton system designed to enhance immersive experiences in virtual and augmented reality by providing realistic tactile feedback, overcoming the limitations of current consumer-grade and professional devices [1]. System Design: Rope-Driven Mechanism and Modular Structure - Kinethread utilizes a computer-controlled electric reel and rope transmission mechanism, combined with a modular tactical vest for load distribution, enhancing comfort during prolonged wear [2]. - The system integrates 10 electric reels, with 8 positioned around the waist to optimize ergonomic design and effectively hide reverse tension during operation, allowing clearer perception of force feedback [2]. Motor Selection and Weight Considerations - The system employs two types of high-torque brushless DC motors, with the larger motor weighing 265 grams and providing a maximum pull of 42N, while the smaller motor weighs 140 grams with a maximum pull of 17N [4]. - The total weight of the system, including the battery, is kept below 5 kilograms, with a wear time of under 30 seconds, balancing performance and practicality [4]. Pulley Mechanism and Force Output - The design incorporates traditional mechanical structures like pulleys to change force direction and provide mechanical advantage, achieving a maximum output force of 120N through a three-pulley structure on the back [6]. - The system's design allows for dual-direction drive from a single motor, reducing complexity and overall weight [6]. Control and Software Capabilities - Each motor connects to a custom driver, with multiple microcontrollers communicating with the host via USB, utilizing the open-source SimpleFOC library for closed-loop control at approximately 2kHz [11]. - The software, developed on Unity, supports various haptic feedback modes, allowing for simultaneous simulation of vibrations and dynamic forces, enhancing the immersive experience [11]. Performance Metrics - Kinethread demonstrates potential for consumer applications with performance tests showing peak force achieved within 50 milliseconds and a vibration feedback bandwidth of 200Hz, capable of producing over 3N of force at 100Hz [12]. - The system's standby power consumption is 1.5W, with typical scene power consumption averaging 10.9W, allowing for over 6 hours of wireless operation with a 12V 5600mAh lithium battery [12]. Application Scenarios - Kinethread can simulate various tactile effects, including static weight, dynamic forces, impact forces, and social interactions, enhancing user experience in virtual environments [13]. User Experience Evaluation - A user study with 12 participants indicated that the combination of vibration and dynamic feedback significantly outperformed other conditions in terms of realism, immersion, and instinctive reactions, highlighting the importance of dynamic feedback [15]. Future Prospects - Future developments aim to address limitations such as the inability to simulate pushing forces and potential risks associated with cable routing, while exploring additional types of force feedback and optimizing motor configurations for improved realism [16].

Core Insights - The article discusses the advancements in embodied AI, particularly the integration of large language models (LLMs) and world models (WMs) to achieve human-like understanding and interaction in physical environments [1][22]. Understanding Embodied Intelligence - Embodied intelligence differs from traditional AI as it actively interacts with the physical world, utilizing sensors for perception, cognitive systems for processing experiences, and actuators for actions, forming a closed loop of perception, cognition, and interaction [2][4]. - The ultimate goal of embodied intelligence is to approach human-level general intelligence, enabling robots to adapt autonomously in dynamic and uncertain environments [4]. Transition from Unimodal to Multimodal - Early embodied intelligence systems relied on single modalities, leading to limitations in performance [5][7]. - The shift to multimodal systems integrates various sensory inputs (visual, auditory, tactile) to enhance task handling capabilities, allowing robots to perform complex tasks more flexibly [8][9]. Core Technologies: LLMs and WMs - LLMs provide semantic understanding, enabling robots to comprehend and plan tasks based on human language, while WMs simulate physical environments to predict outcomes of actions [9][10]. - The combination of LLMs and WMs addresses the shortcomings of each technology, facilitating a more comprehensive approach to embodied intelligence [12][19]. Applications of Embodied Intelligence - In service robotics, modern robots can understand complex instructions and adapt their actions in real-time, improving efficiency and user interaction [20]. - In industrial settings, robots can switch tasks without reprogramming, thanks to the integration of LLMs and WMs, enhancing operational flexibility [20]. Future Challenges - Embodied intelligence requires extensive human-labeled data for training and must evolve towards autonomous learning and exploration in new environments [21]. - Hardware advancements are necessary to support real-time processing of multimodal data, emphasizing the need for efficient chips and low-latency sensors [21]. - Safety and interpretability are critical as robots interact directly with humans, necessitating traceable actions and adherence to ethical standards [21].

Core Viewpoint - The article highlights the innovative developments in Shenzhen's robotics industry, showcasing how technology is being integrated into daily life and redefining service standards in the sector [1][19]. Group 1: Robotics Innovations - The "Robot 6S Store" in Longgang, Shenzhen, offers a unique service model that includes sales, spare parts supply, after-sales service, information feedback, rental, and personalized customization, creating a comprehensive service ecosystem [7][9]. - The store features hundreds of robots and components, with major robotics companies showcasing their products, breaking down barriers between robots and everyday life [7][9]. - The article mentions the evolution of exoskeleton robots, which can now lift weights of up to 20 kilograms, demonstrating their practical applications in various fields such as elderly assistance and industrial protection [5][9]. Group 2: Industry Growth and Ecosystem - Shenzhen's Nanshan Robot Valley is home to over 100 robotics companies, showcasing the city's rapid innovation pace, where prototypes can be developed within a day [10][17]. - The city has established itself as a leader in the low-altitude economy, with 1,058 takeoff and landing points and 309 flight routes, housing over 1,900 companies in this sector [10][17]. - The article notes that the number of AI companies in Longgang exceeds 620, and the robotics industry cluster has over 12,700 companies, indicating significant growth in the sector [17]. Group 3: Market Adaptation and Future Outlook - The article emphasizes that the robotics industry is transitioning from technological breakthroughs to large-scale implementation, with expectations that prices for household and educational robots will significantly decrease in the next 3 to 5 years, making them commonplace like smartphones [9][17]. - Shenzhen's innovation model is market-driven, allowing for rapid adaptation and quick market entry for new products, as highlighted by experts in the article [13][17]. - The integration of technology into urban life is evident through various smart city initiatives, such as facial recognition systems and automated libraries, showcasing Shenzhen's commitment to embedding technology in daily activities [17].

Core Viewpoint - The emergence of ophthalmic surgical robots addresses the high precision and stability requirements in eye surgeries, significantly reducing risks associated with human error and enabling complex procedures that were previously deemed too risky [1][2]. Technological Advancements - The rapid development of embodied AI is transforming ophthalmic surgical robots from mere tools to autonomous surgical partners capable of environmental perception, decision-making, and execution [2][7]. - Future robots are expected to achieve full autonomy in procedures, enhancing efficiency and standardization, particularly in resource-limited areas [2]. Types of Robotic Configurations - Current ophthalmic surgical robots are primarily categorized into single-arm collaborative systems and dual-arm master-slave systems, each catering to different clinical needs [3][5]. - Single-arm systems, such as those from Preceyes and domestic companies, focus on high-precision tasks like retinal injections and are characterized by their simplicity and quick learning curves [3]. - Dual-arm systems, represented by companies like Forsight Robotics and Horizon Surgical Systems, align more closely with traditional surgical practices and support more complex procedures, aiming to create comprehensive ophthalmic surgical platforms [5]. AI Integration and Autonomy - Integrating AI, particularly computer vision and autonomous decision-making, is crucial for transitioning surgical robots from auxiliary tools to fully autonomous entities [7]. - Companies like Forsight and Horizon Surgical Systems are making strides in autonomous cataract surgeries, with clinical trials expected to commence in the near future [7][9]. Global and Domestic Progress - The ophthalmic surgical robot sector is characterized by a collaborative ecosystem involving multiple companies and research institutions [8]. - Internationally, companies like Forsight and Preceyes are leading in clinical validations, while domestic firms like 微眸医疗 and 衔微医疗 are actively conducting clinical trials for high-precision applications [9][10]. Industry Integration and Future Outlook - The acquisition of Preceyes by Zeiss highlights the trend towards integrating surgical robots with imaging and navigation systems, indicating a shift towards a fully digital and intelligent surgical environment [11]. - The future of ophthalmic surgery is expected to be dominated by companies that can integrate across product lines, covering the entire diagnostic and surgical process [11].

Core Viewpoint - The article discusses the introduction of a new strategy called "State-free Policy" in visuomotor control for robots, which enhances spatial generalization capabilities by removing state information from the input, relying solely on visual observations [1][10][24]. Group 1: State-free Policy Overview - The State-free Policy allows robots to perform tasks effectively even when the training data is strictly controlled, such as fixed desktop height and object positions [3][10]. - This policy is based on two key conditions: representing actions in a relative end-effector space and ensuring comprehensive visual input for task observation [11][13]. Group 2: Experimental Results - Extensive experiments demonstrated that State-free Policy significantly improves spatial generalization, achieving a success rate of 0.98 in height generalization and 0.58 in horizontal generalization for the pen insertion task [14][24]. - In challenging tasks like folding clothes and fetching bottles, State-free Policy outperformed state-based models, showcasing superior horizontal generalization capabilities [17][20]. Group 3: Advantages of State-free Policy - State-free Policy exhibits higher data utilization efficiency, maintaining performance even with limited data, unlike state-based strategies that tend to overfit [20][21]. - The policy also shows advantages in cross-platform adaptation, requiring less adjustment compared to state-based strategies, leading to faster convergence and higher success rates [21][22]. Group 4: Sensor Design Considerations - The research suggests reevaluating sensor designs, particularly the necessity of overhead cameras, as they may introduce performance issues due to changes in object positions [22][23]. - The findings indicate that using dual wide-angle wrist cameras can provide sufficient task observation without the overhead camera, maintaining high success rates in various scenarios [23].

Core Insights - A significant moment for Chinese research was highlighted by the publication of five impactful studies in the field of flexible electronics in the prestigious journal "Science Advances" on the same day, with one study even gracing the cover [1][2] - Flexible electronics, characterized by their "light, thin, flexible, and transparent" properties, are expected to play a crucial role in various key sectors such as aerospace, public safety, national defense, and healthcare, providing essential technological support for new productivity [1] - By 2028, the application scale of Chinese-manufactured flexible electronics in the IoT sector is projected to exceed $300 million, capturing approximately 40% of the overall flexible electronics market in the next 10-15 years, establishing itself as a vital pillar of the national strategic emerging industries [1] Group 1: Tsinghua University Team's Progress - Tsinghua University's team developed a magnetic-driven flexible battery-integrated robot, showcasing a capacity retention rate of 57.3% after 200 cycles, with a deployment area of 44.9% on the robot [5][6] - The integration method maximizes functional area utilization, enabling the soft robot to demonstrate embodied intelligence in underwater environments, including disturbance correction and temperature monitoring [6][8] Group 2: ShanghaiTech University Team's Breakthrough - The ShanghaiTech University team reported a 3D-printed multimodal sensing flexible bio-electronic interface that combines adaptive machine learning algorithms, enhancing interaction pathways from control to tactile feedback in robotic prosthetics [9][10] - The developed technology allows for low-cost, large-scale manufacturing of flexible devices with integrated sensors, achieving over 98% accuracy in recognizing complex gestures with minimal calibration [10] Group 3: University of Science and Technology of China Team's Innovation - The USTC team created high-performance acoustic transducers inspired by cicada rib structures, addressing the limitations of traditional materials in acoustic sensitivity and stability [12][13] - The research revealed that the alternating structure of soft elastic protein and hard chitin layers in cicada ribs is key to their mechanical performance, leading to the development of a new composite film with superior acoustic properties [15] Group 4: Tsinghua University Team's Assembly Method - Tsinghua University's team proposed a stretch-induced assembly method for 3D mesh materials, facilitating the integration of high-performance electronic devices [16][17] - This innovative approach allows for the creation of highly tunable biomimetic mechanical properties, simulating the stretching characteristics of biological tissues, and has applications in flexible electronics and tissue scaffolding [17] Group 5: Xi'an Jiaotong University Team's Technological Advancement - The Xi'an Jiaotong University team developed a skin-adaptive focused ultrasound transducer array for non-invasive, real-time monitoring of cardiovascular parameters, offering new hope for early detection of heart diseases [19][20] - The technology allows for adaptive focusing of ultrasound beams based on skin curvature, significantly improving the accuracy and reliability of blood flow parameter detection [21]

Core Viewpoint - The article highlights the advancements in humanoid robot bands, showcasing their performances and technological innovations, indicating a growing trend in the integration of robotics in entertainment and cultural events [1][3][5]. Group 1: Robot Bands and Performances - The third-generation He Xuan robot band from Hangzhou gained significant attention at the 2025 World Robot Conference, performing pieces like "Blue and White Porcelain" with precision and artistic expression [1][3]. - The "Little Central Robot Band," a collaboration between CCTV and Stardust Intelligent, made its debut at Shenzhen Bao'an Airport, engaging travelers with a performance of "Jasmine Flower" [7][9]. - The "Superman Band," developed by Hunan Super Energy Robotics Technology Co., performed at the 2025 Internet Yuelu Conference, demonstrating seamless coordination among three humanoid robots [20][22]. Group 2: Technological Innovations - The He Xuan robot band features breakthroughs in core technologies, including high-speed dexterous hands and lightweight humanoid arms, enabling precise musical performances [5][11]. - Stardust Intelligent's robots utilize rope-driven transmission technology, mimicking human tendon movements, achieving high precision in musical execution [11][13]. - The "Panshi Intelligent" robot band employs intelligent MIDI parsing algorithms and AI composition systems, allowing for real-time adaptation to audience emotions and dynamic performances [16][18]. Group 3: Company Developments and Market Position - Stardust Intelligent, established in December 2022, focuses on humanoid robot development and has secured multiple rounds of financing totaling hundreds of millions, aimed at technology R&D and market expansion [13][14]. - Panshi Intelligent has transitioned from educational robotics to cultural performances, successfully integrating their robot band into various events and gaining recognition in the cultural sector [16][18]. - Hunan Super Energy Robotics has developed a competitive edge through its proprietary AI technology and robot operation systems, positioning itself as a key player in the humanoid robotics market [20][22].

Core Insights - The investment and financing heat in the embodied intelligence industry continues to rise, with a consensus that data collection is a critical breakthrough for advancing from L1 specific task intelligence to L2 combined task intelligence and beyond [1][4] Data Collection as a Key Variable - The core goal of embodied intelligence is to enable robots to possess common sense understanding, allowing them to deduce operational logic based on past experiences when faced with unfamiliar objects and tasks, which relies on high-quality, multi-modal interaction data [4][6] - Achieving human-eye-level 3D perception requires constructing a dataset of over 1 billion entries, highlighting the industry's urgent need for efficient and high-quality data collection solutions [3][6] Current Development Stage - Leading domestic companies are still in the early L1 development stage, capable of performing single-position tasks in specific environments, while the π0.5 model has achieved over 60% accuracy in long-range tasks in real home environments, nearing L2 levels [6][12] - The pre-training effect is crucial for the advancement of embodied intelligence technology, directly dependent on the "quantity" and "quality" of data [6][12] Four Core Data Collection Solutions - The selection of data collection solutions in embodied intelligence is fundamentally about balancing "cost, precision, and generalization capability" [7][28] - **Remote Operation**: High precision but high cost, with a complete setup exceeding 200,000 yuan, making it a significant financial burden [8][12] - **Simulation**: Low cost but suffers from distribution shift issues, making it less effective in real-world applications [14][16] - **UMI Multi-modal Sensor Fusion**: A cost-effective choice for SMEs, providing a balance between cost and precision, but limited in full-body motion capture capabilities [19][21] - **Video Learning**: Led by Tesla, this low-cost exploration method captures employee task execution videos, significantly reducing costs compared to remote operation [22][24] Industry Trends and Future Directions - The future trend in data collection for embodied intelligence will likely involve the integration of multiple solutions to achieve a balance of cost, precision, and scale [28] - The ultimate goal is to achieve an "autonomous data loop," where robots can independently complete tasks, collect data, and optimize models without human intervention [28]

Core Viewpoint - Linghou Robot has successfully completed over 100 million RMB in Series A financing, with funds primarily allocated for R&D, laboratory construction, and capacity expansion in the fields of industrial automation and general robotics [1][3]. Company Overview - Linghou Robot, established in 2015, originated as a research department of the listed company Bozhong Precision Engineering, focusing on the development of components for intelligent manufacturing equipment. It is now part of Jiangsu Bozhong Intelligent Technology Group and is recognized as a core supplier of intelligent manufacturing components [3][5]. - The company has been acknowledged as one of the first enterprises meeting the Ministry of Industry and Information Technology's standards for the industrial robot industry and has received provincial-level recognition as a specialized and innovative small and medium-sized enterprise [3]. Team and R&D - The core team includes founder and chairman Dong Hao, who drives technological innovation, and vice presidents Wang Bihan and Chen Dexi, who oversee production and international market expansion, respectively. The company has established R&D centers in Suzhou, Shenzhen, and Silicon Valley, employing over 400 staff, with more than 200 in R&D [5][8]. - Linghou Robot has developed various products, including machine vision systems, direct-drive motors, industrial robots, and mobile robots, which are widely used in industries such as 3C electronics, semiconductors, automotive, and new energy [5][6]. Product and Market Strategy - The company is advancing into the field of embodied intelligence, launching products like deep vision modules and wheeled robot chassis modules. It aims to provide scalable ODM solutions for global clients in the robotics sector [6][8]. - Linghou Robot has established a comprehensive management system, achieving ISO9001 certification and implementing an IPD process to enhance R&D efficiency based on market demand [7]. Future Outlook - With a sales network covering major cities in China and expanding into Southeast Asia, Europe, and North America, Linghou Robot has served over 800 clients. The company plans to focus on independent R&D of key components and strengthen its core competitiveness to become a world-class supplier in the intelligent manufacturing sector over the next 3 to 5 years [8].