第一财经·2025-09-17 14:40Core Viewpoint - The article discusses the emergence of a new role in the robotics industry, akin to an Android operating system, which aims to bridge hardware differences and enable compatibility among various robotic systems for large-scale deployment in real-world scenarios [3][19]. Group 1: Industry Challenges - Different robot manufacturers are entering various application scenarios, but the lack of compatibility among their algorithms and hardware is hindering the transfer of successful experiences across different environments [5][19]. - Companies are investing significant resources in collaboration with robot manufacturers, but the return on investment (ROI) remains uncertain due to inconsistent machine efficiency and high operational costs [5][19]. - The complexity of deploying robots in real-world settings is exacerbated by the need for extensive adjustments and testing for each unique scenario, leading to prolonged proof of concept (POC) cycles [5][12]. Group 2: Middleware Development - Middleware is being developed to act as a unifying layer that can mask hardware differences and allow algorithms to be transferred across different robotic systems without the need for retraining [6][19]. - The middleware aims to serve as a "translator" between various robotic brains and operational commands, facilitating smoother integration and operation [7][8]. - Companies like Annu Intelligent are working on middleware solutions that could potentially streamline the deployment process and enhance the scalability of robotic applications [18][20]. Group 3: Learning and Adaptation - Robots face challenges in adapting to real-world conditions due to the limitations of offline reinforcement learning, which cannot encompass all possible scenarios [12][15]. - Real-time online learning algorithms are being explored to allow robots to learn and adapt during actual operations, thereby reducing the need for extensive offline training [13][15]. - The integration of physical laws into simulation environments is crucial for improving the accuracy of robotic learning and performance in real-world applications [14][15]. Group 4: Industry Dynamics and Future Outlook - Major players like Google and various Chinese companies are investing in middleware solutions, indicating a growing interest in creating standardized frameworks for robotic integration [17][18]. - The future of the robotics industry may hinge on whether a unified "operating system" can emerge, similar to that in the smartphone industry, despite the complexities and differing goals among hardware manufacturers and AI model developers [19][20]. - The success of middleware in bridging the gaps between manufacturers and application scenarios will be critical for achieving large-scale deployment of robotic systems [19][20].