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公开(公告)号：US20220327308A1
公开(公告)日：2022-10-13
申请号：US17448926
申请日：2021-09-27
申请人： Chongqing University , University of Electronic Science and Technology of China , Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd. , Star Institute of Intelligent Systems
发明人： Yongduan Song , Feng Yang , Rui Li , Yiwen Zhang , Haoyuan Zhong , Jian Zhang , Shengtao Pan , Siyu Li , Zhengtao Yu
摘要： The present disclosure relates to a method for recognizing facial expressions based on adversarial elimination. First, a facial expression recognition network is built based on a deep convolutional neural network. On a natural facial expression data set, the facial expression recognition network is trained through a loss function to make facial expression features easier to distinguish. Then some key features of input images are actively eliminated by using an improved confrontation elimination method to generate a new data set to train new networks with different weight distributions and feature extraction capabilities, forcing the network to perform expression classification discrimination based on more features, which reduces the influence of interference factors such as occlusion on the network recognition accuracy rate, and improving the robustness of the facial expression recognition network. Finally, the final expression classification predicted results are obtained by using network integration and a relative majority voting method.
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2.发明申请公开(公告)号：US20230062408A1
公开(公告)日：2023-03-02
申请号：US17503743
申请日：2021-10-18
申请人： Dibi (chongqing) Intelligent Technology Research Institute Co., Ltd. , Star (Chongqing) Intelligent Equipment Technology Research Institute Co., Ltd.
发明人： Yongduan SONG , Lihui TAN , Lei FANG , Shilei TAN , Shuai WANG
摘要： The invention discloses an adaptive path planning method based on neutral networks trained by the evolutional algorithms, the neutral network training method comprises input and output of the data acquired by the mobile sensors installed on the mobile robots as the neutral networks, and training and optimization of the recurrent neutral networks based on the evolutional algorithms; the path planning method refers to the application of the trained neutral networks to the path planning of the mobile robot, the invention effectively improves local quick search capability and global search capability of the algorithms by applying the evolutional algorithms to the optimization of the recurrent neutral networks, so that the robot can plan a rational path in a dense and uncertain environment.
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3.发明申请公开(公告)号：US20220351043A1
公开(公告)日：2022-11-03
申请号：US17448934
申请日：2021-09-27
申请人： Chongqing University , University of Electronic Science and Technology of China , Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd. , Star Institute of Intelligent Systems
发明人： Yongduan Song , Feng Yang , Rui Li , Shengtao Pan , Siyu Li , Yiwen Zhang , Jian Zhang , Zhengtao Yu , Shichun Wang
摘要： The present disclosure discloses an adaptive high-precision compression method and system based on a convolutional neural network model, and belongs to the fields of artificial intelligence, computer vision, and image processing. According to the method of the present disclosure, coarse-grained pruning is performed on a neural network model by using a differential evolution algorithm first, and the coarse-grained space is quickly searched through an entropy importance criterion and an objective function with good guidance to obtain a near-optimal neural network structure. Then fine-grained search space is built on the basis of an optimal individual obtained from the coarse-grained search, and fine-grained pruning is performed on the neural network model by a differential evolution algorithm to obtain a network model with an optimal structure. Finally, the performance of the optimal model is restored by using a multi-teacher multi-step knowledge distillation network to reach the precision of an original model.
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公开(公告)号：US11772264B2
公开(公告)日：2023-10-03
申请号：US17210688
申请日：2021-03-24
发明人： Yongduan Song , Huan Liu , Junfeng Lai , Ziqiang Jiang , Jie Zhang , Huan Chen , Li Huang , Congyi Zhang , Yingrui Chen , Yating Yang , Chunxu Ren , Han Bao , Kuilong Yang , Ge Song , Bowen Zhang , Hong Long
CPC分类号： B25J9/163 , B25J9/161 , G05B6/02 , G05B13/027
摘要： The present disclosure discloses a neural network adaptive tracking control method for joint robots, which proposes two schemes: robust adaptive control and neural adaptive control, comprising the following steps: 1) establishing a joint robot system model; 2) establishing a state space expression and an error definition when taking into consideration both the drive failure and actuator saturation of the joint robot system; 3) designing a PID controller and updating algorithms of the joint robot system; and 4) using the designed PID controller and updating algorithms to realize the control of the trajectory motion of the joint robot. The present disclosure may solve the following technical problems at the same time: the drive saturation and coupling effect in the joint system, processing parameter uncertainty and non-parametric uncertainty, execution failure handling during the system operation, compensation for non-vanishing interference, and the like.
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公开(公告)号：US20220152817A1
公开(公告)日：2022-05-19
申请号：US17210688
申请日：2021-03-24
发明人： Yongduan SONG , Huan LIU , Junfeng LAI , Ziqiang JIANG , Jie ZHANG , Huan CHEN , Li HUANG , Congyi ZHANG , Yingrui CHEN , Yating YANG , Chunxu REN , Han BAO , Kuilong YANG , Ge SONG , Bowen ZHANG , Hong LONG
摘要： The present disclosure discloses a neural network adaptive tracking control method for joint robots, which proposes two schemes: robust adaptive control and neural adaptive control, comprising the following steps: 1) establishing a joint robot system model; 2) establishing a state space expression and an error definition when taking into consideration both the drive failure and actuator saturation of the joint robot system; 3) designing a PID controller and updating algorithms of the joint robot system; and 4) using the designed PID controller and updating algorithms to realize the control of the trajectory motion of the joint robot. The present disclosure may solve the following technical problems at the same time: the drive saturation and coupling effect in the joint system, processing parameter uncertainty and non-parametric uncertainty, execution failure handling during the system operation, compensation for non-vanishing interference, and the like.
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公开(公告)号：US20220404836A1
公开(公告)日：2022-12-22
申请号：US17403243
申请日：2021-08-16
申请人： Chongqing University , Star Institute of Intelligent Systems , Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd.
发明人： Yongduan Song , Congyi Zhang , Lihui Tan , Junfeng Lai , Saiyu Wang , Yankai Zhang
IPC分类号： G05D1/02
摘要： The present disclosure discloses a method for route optimization based on dynamic window and redundant node filtering, comprising using an existing raster map data set to determine the coordinate information of a starting position and a destination position of movement, and to mark a destination node and an obstacle node in the raster map; using A* algorithm to plan a global route; globally optimizing the global route planned by A* algorithm, and filtering redundant nodes out; combining a dynamic window algorithm to perform the local optimization section by section on the optimized global route so as to obtain a final global route. According to the present disclosure, the combination of algorithms reduces a single movement duration of a mobile robot and improves the smoothness of the movement route curve. At the same time, the problems of the robot occurring on the route during the static driving are alleviated.
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公开(公告)号：US20220403612A1
公开(公告)日：2022-12-22
申请号：US17397459
申请日：2021-08-09
申请人： Chongqing University , Star Institute of Intelligent Systems , Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd.
发明人： Yongduan Song , Hong Long , Junfeng Lai , Fang Hu , Ke'er Chen
IPC分类号： E01H5/09
摘要： 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：US20220341109A1
公开(公告)日：2022-10-27
申请号：US17369412
申请日：2021-07-07
发明人： Yongduan Song , Hong Long , Fang Hu , Jiangyu Wu , Ziqiang Jiang , Junfeng Lai
摘要： A snow shovel structure of a snow plow robot is provided. The snow shovel structure includes a housing where a snow shovel mechanism is. The snow shovel mechanism extends outside the housing and includes a first motor fixed on a top of the housing. The first motor is fixedly connected with a telescopic rod through an output shaft. A second motor is further provided on a top portion of an inner chamber of the housing, and a horizontal plate is fixedly arranged on a side wall of the inner chamber of the housing.
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公开(公告)号：US20220196459A1
公开(公告)日：2022-06-23
申请号：US17491216
申请日：2021-09-30
申请人： Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd. , Star Institute of Intelligent Systems
发明人： Yongduan Song , Yujuan Wang , Gonglin Lu , Shilei Tan , Yating Yang , Chunxu Ren , Mingyang Liu
摘要： The present disclosure provides a real-time vehicle overload detection method based on a convolutional neural network (CNN). The present disclosure detects a road driving vehicle in real time with a CNN method and a you only look once (YOLO)-V3 detection algorithm, detects the number of wheels to obtain the number of axles, detects a relative wheelbase, compares the number of axles and the relative wheelbase with a national vehicle load standard to obtain a maximum load of the vehicle, and compares the maximum load with an actual load measured by a piezoelectric sensor under the vehicle, thereby implementing real-time vehicle overload detection. The present disclosure has desirable real-time detection, can implement no-parking vehicle overload detection on the road, and avoids potential traffic congestions and road traffic accidents.
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公开(公告)号：US12098945B2
公开(公告)日：2024-09-24
申请号：US17491216
申请日：2021-09-30
申请人： Dibi (Chongqing) Intelligent Technology Research Institute Co., Ltd. , Star Institute of Intelligent Systems
发明人： Yongduan Song , Yujuan Wang , Gonglin Lu , Shilei Tan , Yating Yang , Chunxu Ren , Mingyang Liu
CPC分类号： G01G19/024 , G06N3/04 , G06N3/082
摘要： The present disclosure provides a real-time vehicle overload detection method based on a convolutional neural network (CNN). The present disclosure detects a road driving vehicle in real time with a CNN method and a you only look once (YOLO)-V3 detection algorithm, detects the number of wheels to obtain the number of axles, detects a relative wheelbase, compares the number of axles and the relative wheelbase with a national vehicle load standard to obtain a maximum load of the vehicle, and compares the maximum load with an actual load measured by a piezoelectric sensor under the vehicle, thereby implementing real-time vehicle overload detection. The present disclosure has desirable real-time detection, can implement no-parking vehicle overload detection on the road, and avoids potential traffic congestions and road traffic accidents.
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