Abstract: The present disclosure discloses an autonomous mobile grabbing method for a mechanical arm based on visual-haptic fusion under a complex illumination condition, which mainly includes approaching control over a target position and feedback control over environment information. According to the method, under the complex illumination condition, weighted fusion is conducted on visible light and depth images of a preselected region, identification and positioning of a target object are completed based on a deep neural network, and a mobile mechanical arm is driven to continuously approach the target object; in addition, the pose of the mechanical arm is adjusted according to contact force information of a sensor module, the external environment and the target object; and meanwhile, visual information and haptic information of the target object are fused, and the optimal grabbing pose and the appropriate grabbing force of the target object are selected.

Abstract: The present invention discloses a pipeline patrol inspection robot having variable tracks and a control method therefor. The pipeline patrol inspection robot of the present invention includes a robot body, track assemblies symmetrically disposed on a left side and a right side of the robot body, and a movement driving mechanism. The robot body is connected to the track assemblies on the left side and the right side by track fixtures, and track angle adjusting mechanisms are respectively connected between the robot body and the track assemblies on the left side and the right side. By means of the present invention, a track camber angle can be adjusted. In addition, each track angle adjusting mechanism is independent, and has desirable flexibility to adapt to different pipeline environments.

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 ?, ?, ?, and ? 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.

Abstract: Provided are a multi-degree-of-freedom myoelectric artificial hand control system and a method for using same. The system comprises a robotic hand, a robotic wrist (2), a stump receiving cavity (1) and a data processor (3), wherein the robotic hand and the stump receiving cavity (1) are respectively mounted on two ends of the robotic wrist (2); a multi-channel myoelectric array electrode oversleeve, a control unit circuit board, and a battery are connected in the stump receiving cavity (1); and the other end of the control unit circuit board is connected to the robotic hand and the robotic wrist (2).

Abstract: A virtual scene interactive rehabilitation training robot based on a lower limb connecting rod model and force sense information and a control method thereof are disclosed. The thigh, calf and foot of a leg of a human body are equated to a three-connecting rod series-connected mechanical arm. A human body leg gravity compensation model is constructed. The leg posture of a patient is detected by Kinect. An interaction force between a limb of the patient and a rehabilitation robot is detected by a force sensor on the rehabilitation robot. Then, a progressive rehabilitation training method is designed for the model. According to a set weight reduction ratio, the motion of the rehabilitation robot is controlled by judging plantar force data.

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.

Abstract: The present invention provides a two-degree-of-freedom rope-driven finger force feedback device. The two-degree-of-freedom rope-driven finger force feedback device includes a hand support mechanism, a thumb movement mechanism, an index finger movement mechanism, and a handle mechanism. The hand support mechanism includes a motor, a motor shaft sleeve, a sliding rail, and an inertial measurement unit (IMU) sensor. The thumb movement mechanism includes a long rotary disc, a torque sensor, an angle sensor, a thumb sleeve, a pressure sensor, two links, a thumb brace, and a thumb fixing ring. The handle mechanism includes a cylindrical handle, a pressure sensor, a flexible fixing band, and a slider. Torque is driven between the rotary disc and the motor by using a rope. The handle mechanism is movable forward and backward and is capable of automatic restoration.

Abstract: The present invention discloses a high-precision and miniaturized on-orbit calibration device for a six-dimensional force sensor of a space station manipulator and a calibration method thereof, which include an inverted ? shape fixing bracket, three force applying devices, and a cubic stress block. Each force applying device includes a force applying head, a single axis force sensor, a force source part and a fastening part. The force source part includes an upper support plate, a second electrode plate, piezoelectric ceramic plates, a first electrode plate and a lower support plate, which are coaxially arranged sequentially from top to bottom. The single axis force sensor is mounted on the top of the upper support plate, and the hemispherical force applying head is mounted on the top of the single axis force sensor. The cubic stress block is mounted on the top of the six-dimensional force sensor.

Abstract: A whisker sensor includes an upper circuit board, a lower circuit board, a flexible whisker, and a magnet. The magnet is fixed to the flexible whisker through a central through hole, and the location of the magnet changes with the swinging of the whisker; the upper and lower circuit boards are identical in shape and size, and are connected through an upright column. A circular hole is formed at the center of the upper circuit board, four Hall sensors are symmetrically distributed on the edge of the circular hole, and the displacement of the whisker in X and Y directions can be obtained by detecting the change in magnetic field generated by the change in location of the magnet; a contact sensor is mounted on the lower circuit board, and is connected to the whisker through a connecting piece, to detect displacement of the whisker in the Z direction.

Abstract: A virtual reality-based caregiving machine control system includes a visual unit, configured to obtaining environmental information around a caregiving machine, and transmitting the environmental information to a virtual scene generation unit and a calculation unit; the calculation unit, configured to receiving control instructions for the caregiving machine, and obtaining, by calculation according to the environmental information, an action sequence of executing the control instructions by the caregiving machine; the virtual scene generation unit, configured to generating a virtual reality scene from the environmental information, and displaying the virtual reality scene on a touch display screen in combination with the action sequence; and the touch display screen, configured to receiving a touch screen adjusting instruction for the action sequence and feeding back same to the calculation unit for execution, and receiving a confirmation instruction for the action sequence.

Abstract: A natural human-computer interaction system based on multi-sensing data fusion comprises a MEMS anti tracking device, a visual tracking device, a force feedback device and a PC terminal. The MEMS arm tracking device is composed of three sets of independent MEMS sensors for collecting arm joint angle information and measuring an arm motion trajectory. The visual tracking device is composed of a binocular camera for collecting image information and measuring a finger motion trajectory. The force feedback device is mounted in a palm of an operator for providing a feedback force to the finger. The PC terminal comprises a data display module, an arm motion calculating module, an image processing module, a mechanics calculating module and a virtual scene rendering module. The system tracks the arm motion trajectory and the finger motion trajectory of the operator and provides force feedback interaction to the finger of the operator.

Abstract: Brain-computer interface method and system include displaying and providing a motor imagery task to a subject, and collecting a generated digital electroencephalogram signal; reading the digital electroencephalogram signal, performing interception if a preset time period is exceeded, and performing continuous reading if not; performing band-pass filtering, obtaining time-frequency characteristics of the digital electroencephalogram signal, and extracting a frequency value with highest frequency energy as a main frequency; obtaining an instantaneous phase of the digital electroencephalogram signal; generating predicted sine waves by respectively using the main frequency and the instantaneous phase as a frequency and an initial phase of sine waves, and predicting and obtaining real-time phase information; and judging whether the real-time phase is in a vibration stimulation application phase interval, generating and outputting a control instruction, and controlling a vibration motor to vibrate and to stimulate

Abstract: A method for generating a geometric folding full coverage path for a robot is provided. A conventional full coverage path planning algorithm is based on a zigzag pattern, a spiral pattern or a combination thereof. A traversal order is restricted by a linear traversal manner or a traversal manner from inside to outside and therefore lacks flexibility. In the method, a geometric folding operation is used to generate a full coverage path pattern for the robot, referred to as a geometric folding path pattern. The full coverage path has a flexible traversal order. A representation method for the geometric folding path pattern is modeled in the method, and subsequently the method for randomly generating the geometric folding full coverage path and a search method for a geometric folding path within a constraint of passing through specified points in a given order are provided.

Abstract: An autonomous catapult-assisted take-off, recycling, and reuse device and method of a flapping-wing unmanned aerial vehicle (UAV) are provided. The device includes a base, an attitude adjusting mechanism, a catapult mechanism, a recycling mechanism, a control processing unit, a power supply module, and a sensor unit, where the attitude adjusting mechanism includes a connector, a counterweight, an adjusting motor, an attitude adjusting input gear, an attitude adjusting output gear, an attitude adjusting output gear shaft, and an installation platform; the catapult mechanism includes a catapult motor, a catapult motor frame, a pulley, a pull rope, a winch, a pull rope fixing part, a flapping-wing aircraft fixing part, two slide bars, two compression springs, and a catapult gear set; and the recycling mechanism includes a recycling motor, a recycling mechanical arm, a recycling platform, two sprockets, and a recycling gear set.

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.

Abstract: A rope-driven soft hand function rehabilitation device includes four finger exoskeleton mechanisms, a thumb exoskeleton mechanism, and a soft rubber glove. An index-finger exoskeleton mechanism includes an index-finger distal phalanx loop, an index-finger middle phalanx loop, and an index-finger proximal phalanx loop which are mutually connected via a hinge structure. The thumb exoskeleton mechanism includes a thumb proximal phalanx loop and a thumb distal phalanx loop which are connected via a hinge structure. The rope is fastened to the hand function rehabilitation device via an aluminum sleeve which prevents the rope from slipping off during finger flexion/extension and abduction/adduction when the fingers are pulled by the rope at the palm and the hand back.

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.

Abstract: A method for reducing hysteresis error and high frequency noise error of capacitive tactile sensors includes the following steps: step 1: calibration, specifically including positive stroke calibration to form n positive stroke curves and negative stroke calibration to form n negative stroke curves; step 2: averaging, specifically including positive stroke averaging to form an average positive stroke curve, negative stroke averaging to form an average negative stroke curve, and comprehensive averaging to form a comprehensive stroke curve; step 3: fitting modeling, to obtain a positive stroke fitting function, a negative stroke fitting function, and a comprehensive fitting function; step 4: measurement; step 5: noise filtering; step 6: stroke direction discrimination; and step 7: resolving, to obtain the force at the current time by using a corresponding fitting function based on the stroke direction discrimination result.

Abstract: A flexible finger-wearable haptic feedback device includes a fingertip sleeve sheathing a distal phalanx of a finger, a middle sleeve sheathing a middle phalanx of the finger, a proximal sleeve sheathing a proximal phalanx of the finger, outer and inner transmission rods having bending elasticity. The outer transmission rod is fixed on the fingertip sleeve at one end, positioned at a back of a hand at the other end and connected with an outer driver. The inner transmission rod is fixed on the fingertip sleeve at one end, positioned at a palm at the other end and connected with an inner driver. The fingertip sleeve is provided with first and second contact pressure sensors respectively connected with the ends of the outer and inner transmission rods, and an inner wall of the fingertip finger sleeve contacting the finger is provided with a film pressure sensor.

Abstract: An exoskeleton finger rehabilitation training apparatus includes a housing. A first motor and a second motor are disposed inside the housing. A direction of an output shaft of the first motor is opposite to a direction of an output shaft of the second motor. The output shaft of the first motor is provided with a first motor gear. A right side of the first motor gear is engaged with a first transmission gear. An edge of the first transmission gear is sequentially connected to an index finger sleeve and a middle finger sleeve that are axially arranged. The output shaft of the second motor is provided with a second motor gear. A right side of the second motor gear is engaged with a second transmission gear. An edge of the second transmission gear is sequentially connected to a pinky sleeve and a ring finger sleeve that are axially arranged.