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：US20250077837A1

公开(公告)日：2025-03-06

申请号：US18800117

申请日：2024-08-11

Applicant: SOUTHEAST UNIVERSITY

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

IPC: G06N3/0442 ,  G06F3/01

Abstract: Disclosed is an online estimation method for wrist torque based on neural features and LSTM, including following steps: (1) an experimenter keeps his/her arms stationary and applies torque to a torque sensor through his/her wrist; (2) acquiring data from the torque sensor and high-density surface EMG ((HD-sEMG) synchronously; (3) decomposing the HD-sEMG using a blind source separation algorithm to obtain a motor unit spike train (MUST); (4) constructing input and output vectors on the basis of the original HD-sEMG and the decomposed MUST, performing training of the LSTM, and performing polynomial regression of a discharge rate and torque of a neural feature; and (5) calculating a real-time discharge rate (DR) of the CST using a sliding window approach for real-time estimation of the torque.

公开(公告)号：US20240189995A1

公开(公告)日：2024-06-13

申请号：US18398031

申请日：2023-12-27

Applicant: SOUTHEAST UNIVERSITY

Inventor： Huijun LI ,  Ye LU ,  Aiguo SONG ,  Ye LI ,  Baoguo XU

IPC: B25J9/16 ,  B25J9/10

CPC classification number: B25J9/1633 ,  B25J9/104 ,  B25J9/1653

Abstract: A cable force control method includes: establishing a friction model, and calibrating parameters; and calculating the parameters in real time, and controlling a force: identifying the parameters according to the friction model to obtain parameters of an auxiliary cable Bowden system and a power Bowden system: a friction coefficient μa of the auxiliary cable Bowden system, and a friction coefficient μp of the power cable Bowden system; calculating the auxiliary cable Bowden system θa in real time according to the model and a force value of a sensor, and using same as a cable bending angle of the power cable Bowden system θ; and obtaining an inverse control formula Fin=Fout·e−uλθ according to the friction model, and bringing the power cable Bowden system θp into the inverse control formula to serve as a feedforward controller, so as to achieve an effect of real-time force control.

公开(公告)号：US20230211504A1

公开(公告)日：2023-07-06

申请号：US17774317

申请日：2022-01-06

Applicant: SOUTHEAST UNIVERSITY

Inventor： Aiguo SONG ,  Jianwei LAI ,  Huijun LI ,  Hong ZENG ,  Baoguo XU

IPC: B25J9/16

CPC classification number: B25J9/1692

Abstract: The present disclosure discloses an automated calibration system and calibration method for a flexible robot actuator. The calibration system includes a support frame. A visual positioning system, a pressure measuring system and a pneumatic pressure control system are respectively installed on the support frame. The visual positioning system is configured to measure a relative displacement and an angle between two ends of the flexible actuator. The pneumatic pressure control system is configured to charge air into an actuating end of the flexible actuator and measure an input pneumatic pressure of the flexible actuator. The pressure measuring system includes a pressure gauge installed on the support frame through a vertical axis motor system, and the flexible actuator to be calibrated installed on the support frame through a horizontal axis motor system and a rotating motor system. The rotating motor system is installed on the support frame through the horizontal axis motor system, the actuating end of the flexible actuator is fixed on the rotating motor system, and a free end of the flexible actuator is in contact with a measuring end of the pressure gauge to carry out pressure measurement. The calibration system is high in accuracy and simple to use.

公开(公告)号：US20230139608A1

公开(公告)日：2023-05-04

申请号：US17792316

申请日：2022-01-06

Applicant: SOUTHEAST UNIVERSITY

Inventor： Aiguo SONG ,  Jianwei LAI ,  Huijun LI ,  Hong ZENG ,  Baoguo XU ,  Ting WU

IPC: A61H1/02

Abstract: A rehabilitation glove based on a bidirectional driver of a honeycomb imitating structure, including five bidirectional drivers and a cotton glove. The drivers are fixed to a back of the glove through hook and loop fasteners. Each driver includes a hollow buckling air bag in a continuous bent state, a middle guide layer in a continuous bent state and a hollow stretching air bag. The buckling air bag and the middle guide layer are symmetrically arranged, and the stretching air bag in a straightened state is arranged below the middle guide layer. A novel bidirectional driver of a honeycomb imitating structure is provided, which may provide a patient with rehabilitation training in two degrees of freedom: buckling and stretching. A control algorithm of the bidirectional driver is further provided to perform force control output for the driver, which may better help the patient recover hand functions.

公开(公告)号：US20220133578A1

公开(公告)日：2022-05-05

申请号：US17311325

申请日：2020-06-28

Applicant: SOUTHEAST UNIVERSITY

Inventor： Aiguo SONG ,  Jianwei LAI ,  Huijun LI ,  Jianqing LI ,  Baoguo XU ,  Hong ZENG ,  Jun ZHANG

IPC: A61H1/02

Abstract: A exoskeleton finger rehabilitation training device comprises an exoskeleton finger rehabilitation training mechanism comprising a supporting base, a finger sleeve actuating mechanism, and a finger joint sleeve connected to a power output end of the finger sleeve actuating mechanism, wherein the finger joint sleeve can be sheathed at the periphery of a finger joint to be rehabilitated, and the finger joint sleeve can be driven by the power actuation of the finger sleeve actuating mechanism to drive the finger joint to be rehabilitated in order to passively bend or stretch; the supporting base comprises a profiled shell, with an inner surface of the profiled shell being configured based on the profile of the complete back of a palm or part of the back of the palm, and with the back of the profiled shell being provided with a power fixed base.

公开(公告)号：US20250083311A1

公开(公告)日：2025-03-13

申请号：US18827825

申请日：2024-09-08

Applicant: SOUTHEAST UNIVERSITY

Inventor： Baoguo XU ,  Jiajin WANG ,  Xin WANG ,  Weifeng PENG ,  Aiguo SONG

IPC: B25J9/16

Abstract: Disclosed is an optimization modeling and robust control method for a soft robot based on a fusion prediction equation, including the following steps: deriving measurement coordinates based on the fusion prediction equation; designing an observation function based on the measurement coordinates; identifying a Koopman model based on the observation function; and designing a robust model predictive controller based on the Koopman model. Further disclosed are a fusion prediction equation and a derivation method thereof, which can derive correct, abundant but non-redundant measurement coordinates, overcoming the problem of single measurement coordinates in a soft robot system, thereby being conducive to simplifying a design process of the observation function and further improving the accuracy of the Koopman model for the soft robot.

公开(公告)号：US20250076986A1

公开(公告)日：2025-03-06

申请号：US18817208

申请日：2024-08-27

Applicant: SOUTHEAST UNIVERSITY

Inventor： Baoguo XU ,  Xin WANG ,  Jiajin WANG ,  Aiguo SONG

IPC: G06F3/01 ,  G06V10/80

Abstract: Disclosed are an affective haptic regulation system and method based on multimodal fusion, including a haptic optimal parameter adjustment module, a haptic generation module, a visual-auditory generation module, a multi-physiological signal acquisition module, a multi-sensory signal acquisition module, and a multimodal fusion emotion recognition module. The system can fuse multi-physiological signal features with audio and haptic modal features by acquiring a plurality of physiological signals of a user, accurately identify a current affective state of the user in real time through advanced data processing and analysis technology, seek for a haptic parameter with the help of an optimization theory, and achieve proactive regulation of affective state of the user; and the system can overcome the limitations of traditional subjective scale methods, effectively reduce the influence of unstable physiological signals on emotion recognition results, and significantly improve the accuracy of affective detection in the affective haptic regulation system.