证券日报网讯 1月9日，光电股份（600184）在互动平台回答投资者提问时表示，公司2025年7月发布多 模态感知头，融合可见光、红外热成像、气体检测等多类传感器，具备环境稳像、目标定位与异常行为 识别等能力，可广泛应用于人形机器人、机器狗、无人车及无人机等平台，满足复杂环境下的自主巡检 与智能作业需求。 ...

Group 1 - Tencent's Robotics X Lab has formed a strategic partnership with Yushu Technology to enhance the application of Yushu's robots in various scenarios such as cultural tourism sites, shopping malls, and corporate exhibition halls [2] - The collaboration will leverage Tencent's Tairos embodied intelligent model to support Yushu's robots in providing user-friendly tour guide and shopping services, aiming to set industry benchmarks [2] - Tencent participated in Yushu Technology's Series C financing, which was completed in June 2025, with major investors including China Mobile's fund, Tencent, Alibaba, Ant Group, and Geely Capital [2] Group 2 - The robot tour guide solution developed by both companies has been piloted at the Dunhuang Mogao Caves Digital Exhibition Center and the Shanghai Guoling Law Firm global headquarters [3] - The Yushu G1 AI tour guide robot, equipped with the Tairos model, has started its internship as a guide at the Dunhuang site, providing visitors with cultural insights [3] - At the Shanghai Guoling Law Firm, the G1 robot serves as a guide, offering information about the firm's history and allowing clients to engage in Q&A sessions [3] Group 3 - Other companies have also disclosed collaborations with Yushu Technology, focusing on models, hardware, and ecosystem development [4] - iFlytek announced its partnership with Yushu Technology, providing AI services based on its Super Brain 2030 platform, covering over 500 intelligent robot manufacturers [4] - JD.com launched its first offline store in collaboration with Yushu Technology, featuring products like the Go2 robotic dog and G1 humanoid robot, marking an expansion of the robot ecosystem into offline scenarios [4] - Rockchip has reported a high market share for its flagship product RK3588 in the robotics sector, collaborating with Yushu Technology and other notable clients on various robot forms [4]

原文链接 | https://www.zhihu.com/pin/1984008846390355375 点击下方 卡片 ，关注" 具身智能之心 "公众号 >> 点击进入→ 具身 智能之心 技术交流群 作者丨 CyberSoma 编辑丨具身智能之心 机器人核心技术？微型化，应该是我最近提到最多的词。WuJI HAND在前段时间刷屏的时候，明显感觉到微型直驱电机的集成化这个趋势，毕竟当前电机体积仍制 约人形机器人的手臂空间适配。 2. 感知技术从单一触觉到多模态智能融合 在这个你认为具身智能是通往AGI（通用人工智能）的必经之路吗？回答中我比对过今年3月和11月底的具身智能圆桌讨论，各位大佬不仅强调多模态感知学习效率 超视觉-语言大模型，还提到了多模态数据的重要性，这点不仅限于人形机器人，灵巧手的感知亟待升级优化。 3. 场景化定制的垂直细分 在2025 年 11 月十大机器人技术进展中，阿姆斯特朗机器人公司计划打造通用厨房机器人，从洗碗功能起步，这就是专注吃掉垂直场景中的客户，当前的灵巧手仍 然是偏通用，需要更加垂直到场景中，家庭服务、工业装配、医疗康复等等方向，把任何一个市场吃精吃透，都能打败无效内卷，毕竟 ...

Core Insights - Dr. Chen Long, the Chief Scientist of Xiaomi Auto, has been recognized in the 2025 TR35 list for his groundbreaking work in the field of assisted driving, specifically for introducing the Visual-Language-Action (VLA) model [1][3] - Xiaomi's founder and CEO Lei Jun publicly congratulated Dr. Chen on this achievement, highlighting the significance of his contributions to the industry [1] Group 1 - The TR35 award, initiated in 1999, aims to honor young tech talents who drive future transformations through original technologies, with past honorees including notable figures like Larry Page and Mark Zuckerberg [3] - The evaluation committee noted that Dr. Chen's research provides a new paradigm for next-generation assisted driving systems, evolving them from mere command execution to reliable intelligent agents capable of communication and common-sense reasoning [3] Group 2 - Dr. Chen has a background in autonomous driving research in the UK, focusing on making machine behavior more human-like [3] - He joined Xiaomi in 2025, attracted by the company's "human-vehicle-home ecosystem" strategy and the integration of AI with the physical world [3] - The XLA model, led by Dr. Chen, integrates multi-modal perception, natural language understanding, and behavioral decision-making, enabling assisted driving systems to not only drive but also communicate and think [3] Group 3 - An example of the XLA model's capabilities includes the system explaining its actions, such as "slowing down due to predicting a pedestrian might cross the road" [3] - The XLA model has been implemented in the Xiaomi YU7 vehicle, which features an end-to-end assisted driving system trained on 10 million Clips data, utilizing industry-leading hardware and software configurations [3] - As of mid-2025, Xiaomi Auto has assembled a research and development team of over 1,800 people, tested more than 400 vehicles, and invested 5.79 billion yuan in initial R&D efforts, continuously optimizing algorithms through the Xiaomi AI Lab's Xiaomi MiMo foundational model [3]

Group 1 - The establishment of a technical exchange group focused on embodied intelligence technology, inviting participation from various subfields [1] - The group encompasses nearly 20 sub-directions, including humanoid robots, quadrupeds, robotic arms, and areas such as vla, large models, vln, reinforcement learning, mobile operation, multimodal perception, simulation, and data collection [1] - The invitation encourages collaboration and discussion on technology and industry developments among participants [1]

Core Viewpoint - Yunji Technology officially listed on the Hong Kong Stock Exchange on October 16, 2023, despite facing significant financial challenges and a competitive market landscape [2][18]. Financial Performance - In the first five months of 2025, Yunji Technology reported revenue of 0.88 million yuan, with a net loss of 1.18 million yuan, indicating a loss of 1.5 times the revenue per unit sold [4]. - The company's gross profit margin stands at 39.5%, with sales costs amounting to 0.53 million yuan, representing 60.5% of revenue [14]. - Research and development expenses were 24.98 million yuan, accounting for 28.2% of revenue, while sales and marketing expenses were 30.91 million yuan, making up 35% of revenue [14]. Business Segmentation - Revenue from the main business segments includes 74.4% from robots and functional kits and 25.6% from AI digital systems [9]. - The hotel sector dominates revenue generation, contributing 93.2%, followed by commercial buildings at 1.4% and technology at 0.9% [9]. - Direct sales account for 77.6% of revenue, while distributor sales contribute 22.4% [9]. Market Position and Competition - Yunji Technology holds a market share of 13.9% in the hotel service robot market, where the top five players collectively account for only 27.4% of the market [16][17]. - The hotel robot market is characterized by low concentration and high competition, with significant price wars and limited differentiation among competitors [17]. - The company relies heavily on partnerships with major tech firms like Tencent and Alibaba for its software capabilities, lacking an independent technological ecosystem [17]. Future Outlook - Despite raising nearly 600 million yuan from its IPO, the company faces ongoing annual losses of around 200 million yuan, raising concerns about its financial sustainability [17][18]. - The competitive landscape and the lack of innovative differentiation in its product offerings pose significant challenges for Yunji Technology's future growth and profitability [17][18].

Core Viewpoint - The RoboSense Challenge 2025 aims to systematically evaluate the perception and understanding capabilities of robots in real-world scenarios, addressing the challenges posed by traditional perception algorithms in complex environments [1]. Group 1: Event Overview - The challenge is organized by multiple prestigious institutions, including the National University of Singapore, Nanyang Technological University, and the University of Michigan, among others [4][5]. - It is officially recognized as a competition during the IROS 2025 conference, which will take place in Hangzhou, China [5]. Group 2: Challenge Objectives - The primary goal is to develop socially intelligent autonomous navigation robots that can navigate safely and efficiently in dynamic indoor environments without disrupting human activities [8][10]. - The challenge focuses on creating a perception and navigation system based on RGBD vision and odometry, requiring robots to operate without maps or privileged information [9]. Group 3: Challenge Difficulties - Key challenges include dynamic behavior modeling, social rule encoding, and uncertainty handling in unpredictable environments [12]. - Evaluation metrics will not only consider success rates and path efficiency but also social compliance indicators and collision statistics [12]. Group 4: Recommended Directions - Suggested approaches include using transformer-based social trajectory prediction modules, behavior classifiers for risk assessment, and graph neural networks for multi-target structural modeling [15].

Group 1 - The establishment of a technical exchange group focused on embodied intelligence has been announced, inviting participation from various stakeholders in the field [1] - The group encompasses nearly 20 sub-directions, indicating a broad scope of interest and expertise within the embodied intelligence domain [1] - Participants are encouraged to engage in discussions related to humanoid robots, quadrupeds, robotic arms, and various advanced technologies such as VLA, large models, VLN, reinforcement learning, mobile operations, multi-modal perception, simulation, and data collection [1]

Core Insights - The article discusses the development of LabOS, an AI-XR Co-Scientist platform that integrates artificial intelligence with extended reality technology to enhance scientific research collaboration between AI and human scientists [3][6][29] Group 1: LabOS Overview - LabOS is the first AI Co-Scientist that combines computational reasoning with real-world experiments, utilizing multimodal perception and XR-supported human-machine collaboration [6][9] - The platform consists of four types of AI agents: planning agents, development agents, critique agents, and tool creation agents, enabling a complete research workflow from hypothesis generation to data analysis [9][12] Group 2: Functionality and Applications - LabOS allows AI to "see" what human scientists see, providing real-time assistance during experiments, which transforms laboratories into intelligent collaborative spaces [7][27] - The platform has demonstrated its capabilities in three biomedical scenarios: cancer immunotherapy target discovery, cell fusion mechanism research, and guidance in stem cell engineering [21][23][25] Group 3: Technological Innovations - LabOS incorporates LabSuperVision (LSV) for visual understanding of laboratory environments, achieving over 90% accuracy in error detection during experiments [14][18] - The use of XR glasses facilitates seamless interaction between human scientists and AI, allowing for real-time video transmission and structured guidance [17][20] Group 4: Future Implications - The emergence of LabOS signifies a new era of human-AI collaboration in laboratories, enhancing the speed of discovery and the reproducibility of research [29] - As AI and XR technologies continue to evolve, LabOS is expected to become a standard tool in laboratories, fostering a co-evolution of human intuition and machine learning [29]

Core Insights - Honor's CEO, Li Jian, announced at the Magic8 series product launch that the YOYO intelligent agent currently possesses self-evolution capabilities [1] - The self-developed VLA model, MagicGUI, by Honor features multimodal perception and automated execution planning capabilities, claiming to be overall superior to GPT-4o [1] Company Developments - The introduction of the YOYO intelligent agent marks a significant advancement in Honor's AI technology [1] - The capabilities of the MagicGUI model suggest a competitive edge in the AI landscape, particularly in comparison to existing models like GPT-4o [1]