公开(公告)号：US20250073907A1

公开(公告)日：2025-03-06

申请号：US18810462

申请日：2024-08-20

Applicant: SOUTHEAST UNIVERSITY

Inventor： Baoguo XU ,  Weifeng PENG ,  Qianqian LU ,  Aiguo SONG

IPC: B25J9/16 ,  B25J3/00

Abstract: Disclosed is a safety shared control system based on performance of teleoperator, including a master teleoperation system, a slave robotic manipulator system and a communication module; where the master teleoperation system includes EEG signal measurement of a teleoperator, hand controller operation input, and upper computer software, and the upper computer software includes a graphical user interface (GUI), safety simulation for protecting the safety of a robot, and a PoT model; and the slave robotic manipulator system includes a robotic manipulator, a vision camera and lower computer software, and the lower computer software includes a target recognition algorithm, an autonomous controller, and a shared controller for dynamically allocating human-robot control weights. A safety control system coefficient of the teleoperator is identified through safety simulation prior to actual operation, such that a safety control method for different operating experience is implemented, and safety operation of a teleoperation robot is realized.

公开(公告)号：US20220354411A1

公开(公告)日：2022-11-10

申请号：US17634418

申请日：2020-11-30

Applicant: SOUTHEAST UNIVERSITY

Inventor： Baoguo XU ,  Leying DENG ,  Yifei WANG ,  Xin WANG ,  Aiguo SONG

IPC: A61B5/372 ,  A61B5/00

Abstract: Disclosed is a natural movement electroencephalogram (EEG) recognition method based on source localization and a brain network, which includes the following steps: (1) performing multi-channel EEG measurement for natural movements; (2) preprocessing acquired EEG signals, and extracting the movement-related cortical potential (MRCP), and θ, α, β, and γ rhythms; (3) determining a lead field matrix of the signals, calculating initial solutions of sources by means of L1 regularization constraint, and then performing iteration by means of successive over-relaxation to obtain a source localization result; (4) by using the sources as nodes, calculating PLV between each pair of sources at each time point by means of short-time sliding window, and establishing brain networks; and (5) calculating a network adjacency matrix at each time point and five brain network indicators, introducing these features into a classifier for training and testing, and conducting a statistical test for the brain network indicators. The present disclosure makes improvements to the conventional source localization method by using the T-wMNE algorithm in combination with successive over-relaxation, and establishes brain networks by using the sources as nodes, thus improving the EEG decoding accuracy for natural movements and revealing the neural mechanism of the human body.

公开(公告)号：US20200073472A1

公开(公告)日：2020-03-05

申请号：US16467984

申请日：2018-05-23

Applicant: SOUTHEAST UNIVERSITY

Inventor： Aiguo SONG ,  Huanhuan QIN ,  Huijun LI ,  Baoguo XU ,  Hong ZENG

IPC: G06F3/01 ,  G08B6/00

Abstract: The present invention discloses a minitype haptic rendering method based on active and passive devices, which comprises the following steps of: firstly, calibrating a magnetorheological damper and a direct current motor, and obtaining a relationship between an input current and an output torque; converting an expected force/torque value to a current input of the magnetorheological damper, outputting a corresponding torque through the magnetorheological damper, and applying the torque to a body of an operator through a haptic transmission device; secondly, measuring an actually applied force/torque by a sensor mounted at a force/torque application point, comparing an actually outputted force/torque value with the expected force/torque value, and calculating a force/torque error; and finally, converting the force/torque error to an input signal of the direct current motor, and driving the direct current motor to generate a torque corresponding to the error.

公开(公告)号：US20250073911A1

公开(公告)日：2025-03-06

申请号：US18896856

申请日：2024-09-25

Applicant: SOUTHEAST UNIVERSITY

Inventor： Guangming SONG ,  Feng XIE ,  Juzheng MAO ,  Fei WANG ,  Jun ZHOU ,  Aiguo SONG ,  Gang WU

IPC: B25J11/00 ,  B25J5/00 ,  B25J9/16

Abstract: Disclosed are an embracing crawling robot for detecting an underwater pier of a highway bridge and a detection method therefor. The robot includes a main body, underwater lighting systems, tool compartments, depth metering modules, servo driving wheels, inclination measurement modules, underwater manipulator arms, vision array modules, synchronized stretching and fixing systems, and driven wheels. The robot is capable of crawling around an underwater pier of a highway bridge and operating stably in an underwater environment. After cleaning surface attachments on the underwater pier, the robot performs visual detection of a disease; and after determining type and location information of the disease, the robot will transmit disease information back. The robot is capable of crawling around the underwater pier of the highway bridge stably at any depths, perceiving depth and visual information under high-speed and turbid water conditions, thereby realizing detection of the disease on the underwater pier.

公开(公告)号：US20250072812A1

公开(公告)日：2025-03-06

申请号：US18808099

申请日：2024-08-19

Applicant: SOUTHEAST UNIVERSITY

Inventor： Baoguo XU ,  Zelin GAO ,  Xinhao YANG ,  Aiguo SONG

IPC: A61B5/374 ,  A61B5/00

Abstract: Disclosed is an EEG recognition method for a natural hand movement based on a time-domain and frequency-domain multi-layer brain network, including: (1) acquiring a multi-channel EEG signal of the natural hand movement; (2) preprocessing the multi-channel EEG signal, and extracting a δ wave, a θ wave, a α wave, a β wave, and a γ wave at each time point; (3) constructing a time-domain multi-layer brain network using a wSAR model; (4) calculating the frequency-domain multi-layer brain network using the phase-amplitude coupling; (5) combining the time-domain multi-layer brain network and the frequency-domain multi-layer brain network, and performing standardization; and (6) calculating metrics of the time-domain and frequency-domain multi-layer brain network and a super-adjacency matrix of a decomposed time-domain and frequency-domain multi-layer brain network, inputting the same to a two-layer graph convolutional network (GCN), and fusing manual, shallow, and deep features for analysis.

公开(公告)号：US20240328876A1

公开(公告)日：2024-10-03

申请号：US18648462

申请日：2024-04-28

Applicant: SOUTHEAST UNIVERSITY

Inventor： Aiguo SONG ,  Jingjing XU ,  Yuhan CHEN ,  Baoguo XU ,  Huijun LI

IPC: G01L1/22

CPC classification number: G01L1/2287

Abstract: A six-dimensional force sensor elastomer structure based on improved cross beam includes main beams, first floating beams, second floating beams, square corners and thin film strain gauges. Strain gauges are sputtered on the main beams and the first floating beams to form a plurality of sets of Wheatstone bridges. When an input force/moment of a certain dimension acts on the center of an elastomer, the sensor is deformed and resistance values of strain gauges at corresponding positions change, so that output voltages of corresponding bridges are changed.

公开(公告)号：US20240328873A1

公开(公告)日：2024-10-03

申请号：US18655303

申请日：2024-05-05

Applicant: SOUTHEAST UNIVERSITY

Inventor： Aiguo SONG ,  Jingjing XU ,  Yuhan CHEN ,  Baoguo XU ,  Huijun LI

IPC: G01L1/22

CPC classification number: G01L1/2206 ,  G01L1/2262 ,  G01L1/2287

Abstract: A combined structure for thin film sputtering high-precision six-dimensional force sensor includes a cross beam, a double U-shaped beam, a base, a top cover, a bottom cover and thin film strain gauges. Strain gauges are sputtered on the main beam to form six sets of Wheatstone bridges, with three sets on the cross beam and three sets on the double U-shaped beam. The measurement method of the six-dimensional force sensor is that: an input force/moment of a certain dimension acts on the center of the cross beam and the center of the double U-shaped beam, so that the sensor is deformed and resistance values of strain gauges at corresponding positions change, thereby changing output voltages of corresponding bridges.

公开(公告)号：US20240094072A1

公开(公告)日：2024-03-21

申请号：US18025186

申请日：2022-05-12

Applicant: SOUTHEAST UNIVERSITY

Inventor： Aiguo SONG ,  Jingjing XU ,  Shuyan YANG ,  Baoguo XU ,  Huijun LI ,  Ruqi MA

IPC: G01L1/18 ,  G01L5/1627

CPC classification number: G01L1/18 ,  G01L5/1627

Abstract: A miniature combined multi-axis force sensor structure includes a sensor body, a first shell and a second shell, two horizontal main beams and two vertical main beams are arranged on the periphery of an inner round platform in a cross shape, tail ends of the horizontal main beams and the vertical main beams are each connected to a vertical floating beam, and the horizontal floating beams consist of two thin-walled cambered beams; two ends of the horizontal floating beam are each connected to an outer round platform by means of an annular platform; the sensor body is arranged between the first shell and the second shell; strain gauges are stuck on the horizontal main beams and the vertical main beams to form two Wheatstone bridges; and when force/torque acts on the cross beam, the sensor deforms, and the resistance value of strain gauge at corresponding position changes.

公开(公告)号：US20220111536A1

公开(公告)日：2022-04-14

申请号：US17280305

申请日：2020-04-21

Applicant: SOUTHEAST UNIVERSITY

Inventor： Aiguo SONG ,  Chaolong QIN ,  Jiahang ZHU ,  Linhu WEI ,  Yu ZHAO ,  Huijun LI ,  Baoguo XU

IPC: B25J13/02 ,  G06F3/0338 ,  G06F3/01

Abstract: The present invention discloses a care robot controller, which includes: a controller body that includes slide rails, finger slot sliders and a joystick, wherein the finger slot sliders are movably arranged on the slide rails and configured to receive pressing, and the joystick is configured to control the care robot; a gesture parsing unit configured to parse three-dimensional gestures of the controller body, and control the care robot to perform corresponding actions when the three-dimensional gestures of the controller body are in line with preset gestures; and a tactile sensing unit configured to sense the pressing received by the finger slot sliders and initiate a user mode corresponding to the pressing information, so that the controller body provides corresponding vibration feedback. Thus the user can control the controller efficiently and conveniently, the control accuracy is improved, and effective man-machine interaction is realized.

公开(公告)号：US20210361515A1

公开(公告)日：2021-11-25

申请号：US16969198

申请日：2020-06-12

Applicant: SOUTHEAST UNIVERSITY

Inventor： Aiguo SONG ,  Yiting MO ,  Huanhuan QIN ,  Huijun LI ,  Baoguo XU

IPC: A61H1/02

Abstract: A wearable upper limb rehabilitation training robot with precise force control includes a wearable belt, a multi-degree-of-freedom robot arm, and a control box. The robot is worn on the waist of a person by using a belt, and driven by active actuators, to implement active and passive rehabilitation training in such degrees of freedom as adduction/abduction/anteflexion/extension of left and right shoulder joints and anteflexion/extension of left and right elbow joints. In addition, a force/torque sensor is mounted on a tip of the robot arm, to obtain a force between the tip of the robot arm and the human hand during rehabilitation training as a feedback signal, to adjust an operating state of the robot, thereby realizing the precise force control during the rehabilitation training.