Abstract: An external rotation 3D lidar device and a simultaneous localization and mapping (SLAM) method comprises a 3D hybrid solid-state lidar device that is driven to rotate by an external motor. The device significantly improves the horizontal field of view of the lidar and can be mounted on a ground robot to comprehensively improve its 360-degree environment sensing capabilities. Error-state Kalman filtering and pose graph optimization are combined and the overall framework is divided into two parts: front-end odometry and back-end loop-closure optimization. Therefore, high-frequency odometry that meets the requirements of the robot can be output in real time and cumulative errors can be eliminated through the back-end loop-closure optimization.

Abstract: A method and apparatus is described to push to-be-recommended products onto users' terminals based on similarities in the to-be-recommended products and products in the users' historical records of products. To improve the pushed recommendations various technics are applied, including: using predefined criteria to filter products provided from the users' historical records, applying temporal decay to provide real-time recommendations, removing already obtained products from the to-be-recommended products to be pushed, improving similarity calculations by determining similarity using pairwise variations between products both in and out of the candidates for to-be-recommended products, sorting the to-be-recommended product according to a preset recommendation policy, calculating pairwise variations using multiple types of similarity measures, using weights to determine the to-be-recommended products, and applying a preset recommendation policy based on a given scenario.

Abstract: A method and apparatus is described to push to-be-recommended products onto users' terminals based on similarities in the to-be-recommended products and products in the users' historical records of products. To improve the pushed recommendations various technics are applied, including: using predefined criteria to filter products provided from the users' historical records, applying temporal decay to provide real-time recommendations, removing already obtained products from the to-be-recommended products to be pushed, improving similarity calculations by determining similarity using pairwise variations between products both in and out of the candidates for to-be-recommended products, sorting the to-be-recommended product according to a preset recommendation policy, calculating pairwise variations using multiple types of similarity measures, using weights to determine the to-be-recommended products, and applying a preset recommendation policy based on a given scenario.