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银发赛道里的具身智能:“懂养老”比“像人”更重要
Bei Jing Shang Bao· 2025-07-30 12:49
Core Viewpoint - The essence of intelligent care robots is to address real needs in elderly care rather than merely resembling humans, emphasizing practicality and safety in design [2][4]. Group 1: Industry Overview - The "2025 Beijing Intelligent Care Robot Application Competition" showcased 53 robot products focused on intelligent care, highlighting the growing importance of robotics in addressing aging challenges [1]. - The elderly population in China is projected to reach 310 million by the end of 2024, accounting for 22% of the total population, with expectations to exceed 400 million by 2035 [6][7]. - The demand for elderly care services is significant, with a shortage of over 6 million caregivers, while only 500,000 are currently employed [7]. Group 2: Market Potential - The intelligent care robot market is estimated to reach nearly 25 billion yuan in 2023, with a projected compound annual growth rate of 15%, potentially reaching around 66 billion yuan by 2030 [7]. - Current commercialization of care robots is heavily reliant on institutional demand due to high hardware costs, with single robotic arms costing around 50,000 yuan and full systems exceeding 1 million yuan [7][9]. Group 3: Product Examples - The "Cognitive Micro-Oxygen Chamber" by UBTECH exemplifies a care robot that, while not humanoid, effectively meets the needs of cognitive assessment and physical therapy through innovative technology [5]. - A humanoid robot developed by Haibai Chuan Technology can mimic facial expressions and converse in multiple dialects, enhancing emotional engagement with elderly users [6]. Group 4: Challenges and Opportunities - The industry faces challenges in balancing customized needs of institutions with the scalability of production, leading to increased marginal costs [10][11]. - Data acquisition for intelligent care robots is hindered by the need for on-site collection, which is time-consuming and costly, necessitating a shift towards shared health service data to lower R&D costs [11].