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Patent Agency Ranking
公开(公告)号：US20220403612A1
公开(公告)日：2022-12-22
申请号：US17397459
申请日：2021-08-09
Applicant: Chongqing University , Star Institute of Intelligent Systems , Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd.
Inventor： Yongduan Song , Hong Long , Junfeng Lai , Fang Hu , Ke'er Chen
IPC: E01H5/09
Abstract: Disclosed is a snow shoveling and snow discharging assembly of a snow sweeping robot. The snow shoveling and snow discharging assembly comprises a snow stirring structure, a snow feeding structure and a snow raising structure. Stirring cutters in the snow stirring mechanism are driven by a stirring cutter shaft to stir bottom area snow into a snow feeding pipe of the snow feeding structure, an air blower in the snow feeding structure blows accumulated snow into a snow raising pipe of the snow raising structure through a connecting pipe, the snow raising pipe can be driven by a steering motor to rotate by a certain angle to control the snow raising direction, and a second electric push rod acts to control pitching of the guide part, so that the height of snow during snow raising is controlled.
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公开(公告)号：US11462053B2
公开(公告)日：2022-10-04
申请号：US17349170
申请日：2021-06-16
Applicant: Chongqing University
Inventor： Yongduan Song , Li Huang , Shilei Tan , Junfeng Lai , Huan Liu , Ziqiang Jiang , Jie Zhang , Huan Chen , Jiangyu Wu , Hong Long , Fang Hu , Qin Hu
IPC: G06K9/00 , G06V40/20 , G06T7/73 , G06T7/50 , G06T7/246 , H04N5/232 , G06V40/10 , G06V10/40 , G06V40/16 , B25J9/16 , G06K9/62
Abstract: The present disclosure provides a neural network-based visual detection and tracking method of an inspection robot, which includes the following steps of: 1) acquiring environmental images of a dynamic background a movement process of the robot; 2) preprocessing the acquired images; 3) detecting human targets and specific behaviors in the images in the robot body, and saving the sizes, position information and features of the human targets with the specific behaviors; 4) controlling the orientation of a robot gimbal by using a target tracking algorithm to make sure that a specific target is always located at the central positions of the images; and 5) controlling the robot to move along with a tracked object. The neural network-based visual detection and tracking method of an inspection robot in the present disclosure has a quite high adaptive ability, achieves better detection and tracking effects on targets in a dynamic background scene.
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公开(公告)号：US20220171395A1
公开(公告)日：2022-06-02
申请号：US17443205
申请日：2021-07-22
Applicant: Chongqing University
Inventor： Yongduan Song , Ziqiang Jiang , Shilei Tan , Junfeng Lai , Huan Liu , Li Huang , Jie Zhang , Huan Chen , Hong Long , Fang Hu , Jiangyu Wu , Qin Hu , Wenqi Li
Abstract: A method for obstacle detection and recognition for an intelligent snow sweeping robot is disclosed, comprising: 1) disposing ultrasonic sensors at a front end of the snow sweeping robot to detect distance information from an obstacle ahead; and disposing radar sensors at the front and rear of the snow sweeping robot to detect whether a creature suddenly approaches; 2) processing signals detected by each of the ultrasonic sensors and radar sensors, and calculating a forward distance of the snow sweeping robot; and 3) determining a snow cover extent of a working road, detecting a change of the distance from the obstacles, and recognizing the obstacles for conditions of an ultrasonic ranging variation ratio and a variation of the forward distance of the snow sweeping robot, a change of the signal detected by radar sensors, and a descriptive statistic of the snow cover extent within a specific time period.
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公开(公告)号：US11782448B2
公开(公告)日：2023-10-10
申请号：US17443205
申请日：2021-07-22
Applicant: Chongqing University
Inventor： Yongduan Song , Ziqiang Jiang , Shilei Tan , Junfeng Lai , Huan Liu , Li Huang , Jie Zhang , Huan Chen , Hong Long , Fang Hu , Jiangyu Wu , Qin Hu , Wenqi Li
CPC classification number: G05D1/0214 , E01H5/04 , G01N29/00 , G01S15/00 , G05D1/0255 , G05D1/0257
Abstract: A method for obstacle detection and recognition for an intelligent snow sweeping robot is disclosed, comprising: 1) disposing ultrasonic sensors at a front end of the snow sweeping robot to detect distance information from an obstacle ahead; and disposing radar sensors at the front and rear of the snow sweeping robot to detect whether a creature suddenly approaches; 2) processing signals detected by each of the ultrasonic sensors and radar sensors, and calculating a forward distance of the snow sweeping robot; and 3) determining a snow cover extent of a working road, detecting a change of the distance from the obstacles, and recognizing the obstacles for conditions of an ultrasonic ranging variation ratio and a variation of the forward distance of the snow sweeping robot, a change of the signal detected by radar sensors, and a descriptive statistic of the snow cover extent within a specific time period.
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公开(公告)号：US20220180090A1
公开(公告)日：2022-06-09
申请号：US17349170
申请日：2021-06-16
Applicant: Chongqing University
Inventor： Yongduan Song , Li Huang , Shilei Tan , Junfeng Lai , Huan Liu , Ziqiang Jiang , Jie Zhang , Huan Chen , Jiangyu Wu , Hong Long , Fang Hu , Qin Hu
Abstract: The present disclosure provides a neural network-based visual detection and tracking method of an inspection robot, which includes the following steps of: 1) acquiring environmental images of a dynamic background a movement process of the robot; 2) preprocessing the acquired images; 3) detecting human targets and specific behaviors in the images in the robot body, and saving the sizes, position information and features of the human targets with the specific behaviors; 4) controlling the orientation of a robot gimbal by using a target tracking algorithm to make sure that a specific target is always located at the central positions of the images; and 5) controlling the robot to move along with a tracked object. The neural network-based visual detection and tracking method of an inspection robot in the present disclosure has a quite high adaptive ability, achieves better detection and tracking effects on targets in a dynamic background scene.
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