The 2026 World Robot Conference is currently underway in Beijing's Yizhuang district, drawing massive crowds as over 300 domestic and international companies showcase more than 3,000 exhibits, including more than 300 world-first product debuts. While the robots on display demonstrate impressive capabilities on stage, a pivotal question dominates discussions among attendees: what hurdles must humanoid robots clear to transition from exhibition novelties to everyday consumer products?

Wang Xingxing, founder of Unitree Robotics, made his first public appearance since his company's successful listing. He emphasized that the critical inflection point for general-purpose robots to truly integrate into daily life and households will arrive within the next decade. According to Wang, the primary bottleneck currently lies in the insufficient generalization capabilities of embodied intelligence.

Wang Hao, director of the Industrial Policy Research Institute at the CCID Research Institute under the Ministry of Industry and Information Technology, explained that generalization capability refers to a robot's ability to maintain stable performance in structured production lines while facing sharp declines in reasoning and decision-making when confronted with unknown environments, non-standard objects, or dynamic interference. A truly versatile "brain" requires cross-scenario semantic understanding, long-horizon task planning, and autonomous learning abilities, enabling robots to extrapolate knowledge like humans rather than requiring a separate program for each new scenario. Achieving this demands more efficient model architectures, high-quality datasets, and extensive AI training supported by massive computational resources.

Beyond intelligent processing, robots require exceptionally dexterous hands capable of performing precise operations such as opening bottle caps, folding laundry, and plugging in data cables, all of which demand substantial specialized training. Wan Zhe, a professor at Beijing Normal University, outlined several critical thresholds that must be crossed before humanoid robots can effectively replace human labor. First, the technology barrier: current robots are largely "specialized tools" trained for single scenarios, becoming non-functional when workstations or objects change, with battery life typically limited to just 2 to 4 hours, while dexterous manipulation precision and durability remain far from adequate.

Second, the cost barrier: full-size humanoid robots currently carry price tags ranging from hundreds of thousands of yuan, with industry consensus suggesting that costs must drop below 50,000 yuan per unit to achieve economically viable large-scale replacement, while investment payback periods must shrink to 1 to 2 years. Third, the reliability barrier: industrial applications require annual operational availability exceeding 95 percent, yet most current robots exhibit high failure rates in real-world environments, and safety standards for human-machine coexistence remain incomplete. Fourth, the industrial ecosystem barrier: immature supply chains, high costs of replicating scenarios, and underdeveloped regulatory frameworks all represent hard constraints that must be resolved for scaled deployment.

Over recent years, the industry has enabled robots to stand, run, jump, and master tasks like grasping cups, folding clothes, and moving boxes. Yet the truly difficult work has only just begun. A genuine understanding of the world by an intelligent agent is demonstrated not by repeating a well-practiced action, but by knowing what to do when faced with unfamiliar surroundings, a chair unexpectedly moved, or a person suddenly appearing. The most significant transformation from exhibit to product occurs beyond the exhibition floor—the moment robots step off the stage and into the real world marks the true beginning of embodied intelligence.