奥比中光 vs 速腾聚创：机器人之“眼”的对决

Core Insights - The humanoid robot industry is on the brink of commercialization, with companies like SUTENG and ORBBE focusing on advanced vision solutions [1] - SUTENG emphasizes laser radar for 3D environmental perception, while ORBBE specializes in 3D vision sensors for close-range object recognition [1] - Both companies adopt a "co-opetition" strategy, combining competition and collaboration in the multi-sensor fusion approach [1] Company Strategies - ORBBE launched the Gemini 335/336 series depth cameras and MS600 laser radar, covering various technical routes to meet humanoid robot environment modeling needs [2] - In 2024, ORBBE reported revenue of 564 million yuan, a 56.8% increase year-on-year, while net profit loss decreased by 77.20% [2] - SUTENG aims to be a "robot technology platform company," launching new products like the Active Camera platform and the second-generation dexterous hand [2][3] - SUTENG achieved revenue of 1.649 billion yuan in 2024, a 47.20% increase, with a net loss of 482 million yuan, reducing losses by 88.89% [3] Competitive Landscape - The competition between ORBBE and SUTENG is characterized by short-term implementation capabilities versus long-term technological barriers [4] - ORBBE's 3D vision sensors have established a scalable delivery capability, partnering with leading robot clients like Cloudwise Technology and Qianlong Intelligent [4][5] - SUTENG invested 615 million yuan in R&D in 2024, accounting for 37.3% of total revenue, while ORBBE invested 204 million yuan, making up 36.2% [4] - SUTENG's strategy includes a low-price approach to market expansion, aiming for a "low-cost hardware + value-added services" business model [5] Industry Trends - The humanoid robot sector is entering a new phase of "soft and hard collaboration," with ORBBE's rapid implementation capabilities meeting initial industry demands [5] - The next two years will be crucial for determining which company can achieve breakthroughs in cost control and scene adaptability, potentially leading the value chain distribution in the next robot era [5]