打造上手即用的遥操作机器人，「灵御智能」完成种子＋轮融资丨早起看早期

Core Insights - The article discusses the emergence of "Lingyu Intelligent," a company founded by a team with backgrounds from Tsinghua University and Carnegie Mellon, focusing on high-quality remote operation technology for robots [5][6]. - The company aims to address the challenges of embodied intelligence data collection and promote the rapid deployment of robots in service and industrial sectors through a three-step strategy: selling hardware, data, and capabilities [5][8]. Team Overview - The founder and chief scientist, Mo Yilin, has a strong academic background in automation and robotics, while CEO Jin Ge has experience in both technology entrepreneurship and management [6]. Financing Progress - "Lingyu Intelligent" recently completed a seed round financing of tens of millions, led by Huaying Capital, with participation from existing investors [7]. Products and Business - The company has developed a comprehensive remote operation system that includes three core modules: machine-side hardware, human-side hardware, and a control platform [8]. - The pricing strategy is aimed at different market needs, with the wheeled dual-arm remote operation robot priced around 70,000 yuan, making it accessible for small and medium-sized projects [8][12]. Business Model - "Lingyu Intelligent" has a clear commercialization path through a three-step strategy: selling hardware to gain market share, selling data to create a data barrier, and eventually selling capabilities to provide intelligent solutions [11][12][13]. Key Barriers - The company has achieved breakthroughs in reducing latency and costs, which are critical for the deployment of remote operations [15][16]. - The system's image latency is as low as 100 milliseconds, and operational latency is only 50 milliseconds, meeting the requirements for high-precision tasks [15]. Founder Insights - Mo Yilin believes that remote operation is a necessary step towards fully autonomous robots, emphasizing the importance of easy-to-use robots for high-quality data collection [19][20]. - He highlights the current data challenges in the robotics field, noting that the volume of data is significantly lower than in other sectors like autonomous driving [21]. - The future trend in data collection will lean towards VR devices, which offer high precision and low cost, aligning with human operational habits [23].