盘点第一波人形机器人倒闭潮，谁能活过2026年

Core Viewpoint - The humanoid robot industry in 2025 is experiencing a severe dichotomy, with significant funding and successful companies on one side, while many startups face collapse due to financial and operational challenges [4][5][9]. Industry Overview - In 2025, the humanoid robot sector saw 610 financing events, nearly tripling from the previous year, with total funding exceeding 57 billion yuan [15]. - Over 100 humanoid robot companies in China have differentiated significantly, with leading firms securing billion-level orders and preparing for IPOs, while others struggle to survive [4][5]. Company Failures - Notable failures include K-Scale Labs, which collapsed just before mass production due to cash flow issues, revealing the challenges faced by many startups lacking a complete local supply chain [5][6]. - Rethink Robotics, a pioneer in collaborative robots, faced its second closure in 2025 after failing to meet market expectations, highlighting the risks of rushed product launches [7][9]. - iRobot, the maker of Roomba, filed for bankruptcy in December 2025, attributed to prolonged financial struggles and competition from lower-priced Chinese products [8][9]. Market Dynamics - The industry is shifting from a focus on academic institutions to industrial enterprises, with increased orders from automotive manufacturers, indicating a demand for reliability and economic viability [15][16]. - The competition has intensified, with many companies producing similar products, leading to a "race to the bottom" in pricing and innovation [10][11]. Technological Challenges - The primary bottleneck in humanoid robots is the AI module, which is crucial for their functionality, yet many companies invest little in this area, relying on larger tech firms for support [11][12]. - The rapid pace of technological evolution means that today's leaders can quickly become laggards if they fail to innovate [12][13]. Survival Strategies - Companies must establish differentiation, create genuine commercial loops, maintain financing capabilities, and leverage data to enhance AI models [16]. - The industry is expected to see further consolidation and a clearer divide between successful firms and those unable to adapt to market demands [15][16].