Humanoid robots are moving from science fiction to reality, and visual perception has always been a key bottleneck in their development. Recently, the Beijing Humanoid Robot Innovation Center announced the launch of a revolutionary visual perception system called "Humanoid Occupancy." This technology is considered a major breakthrough in the environmental understanding capabilities of humanoid robots.
For a long time, robot perception systems have faced serious challenges. Most existing perception technologies can only adapt to single or specific scenarios, and they often perform poorly when dealing with complex and changing real environments. More seriously, many systems cannot effectively integrate data from different sensors, leading to the waste of valuable environmental information, and even creating perceptual blind spots, which directly affects the robot's mobility, navigation, and operational accuracy.
The core innovation of the "Humanoid Occupancy" system lies in introducing semantic occupancy representation technology. This technology enables detailed modeling of three-dimensional space, directly describing the occupancy status and object category information of each spatial location through voxel units. Compared with traditional top-down representations, this method provides more three-dimensional and comprehensive environmental information.
The system demonstrates three technical advantages. In terms of spatial information processing, the system achieves complete encoding of the three-dimensional environment, allowing each spatial unit to be accurately identified and classified. In data fusion, semantic occupancy representation naturally supports the collaboration of multi-modal sensors, enabling unified processing and analysis of data collected by RGB cameras, depth sensors, LiDAR, and other devices. In system architecture, the development team optimized sensor configurations, built a dedicated panoramic occupancy perception dataset, and designed an efficient multi-modal fusion network, ensuring the accuracy and response speed of perception.
The project team also addressed the industry's pain point of data scarcity. They built a large-scale dataset covering various application scenarios such as home life and industrial production, and provided detailed semantic annotations. This dataset not only provides a training foundation for the current system, but also offers valuable resources for the entire field of humanoid robot research.
Industry experts believe that the release of the "Humanoid Occupancy" system marks a new stage in the development of humanoid robot perception technology. As this technology matures and is promoted, humanoid robots are expected to play a greater role in areas such as household services, industrial manufacturing, and medical care, truly achieving harmonious coexistence with humans.
From the perspective of technological development, this breakthrough not only solves the current perception challenges faced by humanoid robots, but also lays a solid foundation for the large-scale application of future intelligent robots. With the continuous improvement of related technologies, we may soon witness the historical moment when humanoid robots truly enter households across the world.
Paper link: https://arxiv.org/pdf/2507.20217