Group 1 - Yushu Technology has announced a new patent that enhances the ability of robots to operate in complex environments through a method for dynamic spatiotemporal synchronized mapping based on multi-sensor data fusion, significantly improving spatial registration accuracy and dynamic scene mapping effectiveness [2] - Anhui Wanrui Cold Electric Technology has achieved a breakthrough in helium extraction technology, producing helium gas with a purity of 99.99997% (6N9 level) from natural gas, marking a significant advancement in low-abundance natural gas helium extraction in China [2] - Hunan Fanhang Intelligent Equipment has launched the "Whale" series of supersonic centrifugal compressors, breaking the foreign monopoly in the high-end centrifugal compressor market, which has been dominated by foreign brands accounting for over 80% of the domestic market [2] - China's first commercial SAR satellite with full polarization observation capability, AIRSAT-05, has been successfully launched, featuring an X-band multi-polarization synthetic aperture radar with a maximum imaging resolution better than 1 meter and a maximum observation width exceeding 300 kilometers [2][3]

Core Viewpoint - Hangzhou Yushu Technology Co., Ltd. has announced a patent for a "Dynamic Spatiotemporal Synchronization Mapping Method and System Based on Multi-Sensor Data Fusion," aimed at improving the accuracy of mapping in dynamic environments [1] Group 1: Patent Details - The patent falls under the field of environmental perception technology [1] - Existing mapping solutions based on multi-sensor data do not account for spatiotemporal discrepancies between sensor data, leading to insufficient synchronization during data fusion [1] Group 2: Technological Innovations - The invention includes several modules: point cloud distortion correction module, sensor time alignment module, dynamic target perception module, and multi-map fusion module [1] - These innovations effectively address the issue of insufficient spatiotemporal synchronization in multi-sensor data fusion [1] Group 3: Impact on Robotics - The method significantly enhances the spatial registration accuracy of point clouds and images [1] - It improves the mapping effectiveness in dynamic scenes, enabling robots to accurately identify and track dynamic targets [1] - This advancement increases the autonomous operational capabilities of robots in complex environments [1]