AIRROBO, the smart home appliance brand with a focus on AI-enabled technologies, supported by world-leading AI and humanoid robotic company, UBTECH Robotics, introduced USLAM Air 5.0, the much-anticipated technology empowered by UBTECH Robotics for its robovacs. The USLAM Air 5.0 allows AIRROBO robovacs to intelligently and accurately navigate and position themselves with smarter map building and targets identifying capabilities.
LiDAR technology and SLAM algorithm are the core technologies of any type of robot. UBTECH Robotics’ powerful USLAM technology has empowered the sub-brand AIRROBO, deriving USLAM Air 5.0, which solves real-life problems in household cleaning automation with high efficiency, accuracy and stability, not crashing into chairs and tables before it cleans up nor getting pets tangled and messing up floors, for example.
What is USLAM?
After five years of technological development, UBTECH Robotics possesses a variety of proprietary core techs in the field of humanoid robots, including the multi-source sensor SLAM system, lightweight semantic real-time map reconstruction, scenario-based autonomous perception and comprehension, navigation planning, and decision control. Based on these achievements, UBTECH Robotics has independently developed USLAM (autonomous positioning and navigation system), which integrates the functions of Localization, Mapping, Navigation and Perception. USLAM not only enables a plug-and-play system for multiple sensors, it also makes positioning and navigation more Efficient, Accurate and Stable.
Recommended AI News: NextPlay Announces a Request for Proposals for Its Upcoming Suite of Stable Coins
What is USLAM Air 5.0?
USLAM Air 5.0 is derived from USLAM which has been validated and optimized through application in the field of humanoid robots for 5 years. By supporting Cloud-Based Intelligent Service Robot Cruzr in 2017, Autonomous Indoor Monitoring Robot AIMBOT in 2019, UV-C Disinfection Robot ADIBOT in 2020, and Intelligent Humanoid Service Robot Walker in 2021, UBTECH Robotics’ powerful USLAM system, has promoted the development of positioning and navigation technology and the implementation of a wider range of applications in the robotic industry.
Core Technologies
- Combined laser and visual navigation for large-scene high-quality mapping
- Multi-sensors take account of strong robustness and high accuracy
- Dynamic and timely path-planning and 3D all-round autonomous obstacle avoidance
Recommended AI News: Smart Engines Brings OCR to the Travel Industry in Kazakhstan
UBTECH Robotics empowers AIRROBO by applying the systematic integration of autonomous positioning and navigation technology to smart home appliances like robovacs. Therefore, USLAM Air 5.0 was derived from USLAM. “Air” indicates and symbolizes the lightweight semantic algorithm, which can be interpreted as less requirements on the hardware, due to a more delicate algorithm. “Air” also represents the brand identity of AIRROBO. In practical application, USLAM Air 5.0 enables high-quality mapping in large or small living space, multi-sensor millimeter-level high-precision positioning, dynamic path planning and 3D all-around autonomous obstacle avoidance. In view of the above, AIRROBO robovacs “think, understand and respond” better in terms of mapping, navigation, planning, perception, positioning, cleaning, safety and user experience. (LiDAR technology is a sensing method that uses light in the form of a pulsed laser to measure ranges for better navigation only, protecting users privacy.)
“In recent years, as the pursuit of high standard of living has increased, robot vacuum cleaners in China and the global market have been iteratively upgrading to meet the trend of an aging population, increased pet ownership, and younger residential owners. With smart appliances entering millions of households, different sizes of living space and complex indoor environment have become a challenge for the smart home industry.” said Tommy Zhang, general manager of AIRROBO.
Over the years, UBTECH Robotics has put robots into use in many fields, among which, USLAM has processed more than 100,000 kilometers of course data for accurate navigation in large scenarios. The total area of USLAM’s autonomous map construction has exceeded one million square meters. The positioning accuracy of USLAM has reached centimeter level as well as control accuracy at 1 millimeter level*. USLAM recognizes over a thousand target identifications, and has supported the real-time construction of object-level semantic maps.
Recommended AI News: AscendEX Announces a $50 Million Series B Raise Led by Polychain Capital and Hack VC
Comments are closed.