63 results about "Motion coordination" patented technology

The invention discloses a multi-view child motion coordination ability evaluation system and method based on deep learning, belongs to the technical field of motion evaluation, and solves the problems that child motion evaluation in the prior art mainly depends on manual observation and simple physical testing, and multiple angles and key details of child actions are difficult to synchronously track. The method comprises the following steps: training to obtain a skeleton point detection model and an athletic ability evaluation model, acquiring real-time video streams of personnel entering a field based on an acquisition camera, identifying skeleton key points in a preprocessing data set by the skeleton point detection model, performing multi-person detection on a personnel matching result based on an athletic area division method, and evaluating the athletic ability of the personnel. The exercise ability evaluation model carries out quantitative analysis on multi-person detection results; according to the invention, visual identification and motion state detection technologies are combined, a front view angle and side view angle dual-camera layout is adopted, and a deep learning algorithm is matched, so that automatic children dynamic motion evaluation is realized. The action process can be completely captured, and the detection accuracy and efficiency are improved.

The invention provides a double-machine lifting dynamic balance control method based on real-time load feedback, which comprises the following steps of: after a system is initialized, synchronously acquiring load, height, attitude, position, motion and environment data of two machines, and fusing and filtering; load, height, angle, position and motion coordination multiple deviations are calculated, and balance and safety are evaluated; generating a speed, position, attitude and safety comprehensive control strategy by using multi-objective optimization according to an evaluation result, and setting a priority and a look-ahead mechanism; executing instructions in a distributed manner and monitoring the instructions in real time; self-adaptive parameter adjustment and machine learning continuous optimization are carried out based on a feedback closed loop; and multi-stage safety monitoring and emergency processing are synchronized. According to the invention, the precision, safety and efficiency of hoisting operation can be improved, the operation difficulty and energy consumption are reduced, and the adaptability and reliability of the system in a complex environment are enhanced.

The invention belongs to the technical field of robot control, and particularly relates to a self-adaptive whole-body control method suitable for a quadruped robot in an uncertain dynamic environment, and the method integrates an extended state observer (ESO), a model prediction controller (MPC) and a whole-body controller (WBC) based on hierarchical optimization. And a closed-loop control architecture is constructed to improve the robustness and motion coordination ability of the quadruped robot in a complex environment. Firstly, external disturbance is estimated and compensated in real time through ESO; then, the MPC optimizes future system behaviors in a rolling manner under the condition of considering interference terms, and an expected foot end counter-acting force is output; and finally, the WBC is combined with the priorities of the multiple tasks to generate all joint control instructions in a constraint optimization form, and task collaboration and dynamic adaptation are achieved. The method has the advantages of being high in disturbance self-adaptive capacity, high in control precision, suitable for a multi-task environment and the like, and is particularly suitable for quadruped robot control tasks in complex dynamic scenes such as transportation and search and rescue.

The invention relates to the technical field of motion redundancy parallel robot control, in particular to a method for designing a 2R1T motion redundancy parallel robot high-performance hierarchical synchronous controller based on time delay estimation, which enables a system to estimate current kinetic parameters in real time by introducing a time delay estimation technology, and enables the current kinetic parameters to be estimated in real time in a high-speed motion state. On the basis of the problems of uncertainty, nonlinearity and the like of robot dynamic parameters, dynamic data predicted in real time is used as feed-forward input, so that excessive redundant calculation is avoided, and the efficiency of a control algorithm is optimized; by introducing hierarchical synchronous control, the error difference between redundant degrees of freedom is overcome, the motion precision of a hierarchical driver and the stability of the system are ensured, and the dynamic response of the robot and the robustness of the system are optimized by taking a time delay estimation technology as dynamic feed-forward compensation; and the coordination problem of redundant degrees of freedom is disassembled into a plurality of sub-problems through layered synchronous control, so that the motion coordination and control precision of the robot is improved.

The invention discloses a dexterous hand control device, a dexterous hand control method and a robot, and the dexterous hand control device comprises a communication interface which is used for being connected with an upper computer and receiving a control instruction sent by the upper computer; the whole-hand manager is connected with the communication interface; an independent communication channel is constructed between the multiple finger controllers and the whole hand manager, and connection is established through the communication channel. According to the invention, the plurality of finger controllers are connected with the whole hand manager, so that the whole hand manager can synchronously and coordinately manage the finger controllers, synchronous coordination control on the fingers or the motors is realized when the dexterous hand is controlled, and the action coordination and stability of the dexterous hand are improved.

The invention discloses a mobile audio-visual cooperative unmanned aerial vehicle detection system, and belongs to the technical field of intelligent detection and automatic control. The system comprises a mobile ROS unmanned vehicle platform, an audio-visual perception module, an embedded processing unit and an execution mechanism. The mobile ROS unmanned vehicle platform comprises a motion control system, a serial port communication module and a wireless communication module; the audio-visual perception module comprises an infrared visual acquisition unit and a four-channel audio acquisition array and is used for acquiring infrared image information and acoustic signals of the unmanned aerial vehicle; the embedded processing unit comprises a multi-modal data fusion processor and a motion cooperation controller and is used for synchronously processing the infrared image information and the acoustic signal and generating a control instruction; the execution mechanism comprises a two-degree-of-freedom steering engine holder and a self-adaptive cruise system. According to the invention, through audio-visual cooperation and dynamic mode switching, a fixed detection scene is not needed, continuous tracking of the unmanned aerial vehicle and blind area complement detection can be realized, and detection continuity and accuracy are improved.

The invention discloses a non-contact screening system for motion coordination based on computer vision, which relates to the field of computer vision, and comprises the following steps: acquiring a human body motion image through a non-contact camera, extracting human body key point coordinates frame by frame by using a deep learning algorithm after noise reduction and distortion correction, and constructing a time sequence data set; performing smooth jitter removal and interpolation processing to form standardized data; calculating track, rhythm and stability multi-dimensional motion coordination quantitative characteristics based on the data, and performing comparative analysis with a personal historical database to identify a motion function degradation trend; and based on age groups and scenes, customizing screening parameters, coordinating workflows of the components, and realizing full-process automatic screening. The method has the advantages that invasive and cross infection risks are avoided through non-contact acquisition, accurate and objective assessment of the exercise coordination is realized by means of deep learning and time series data analysis, exercise function degradation can be early warned, and an efficient and reliable scheme is provided for various exercise coordination screening scenes.

The present invention relates to the field of robot motion control and provides an interactive control method and system with frequency adaptability, comprising: a robot obtaining a user's position trajectory and calculating a velocity time series based on the user's position trajectory; constructing a motion model and a feedback controller based on the velocity time series; integrating the motion model and the feedback controller to obtain an integrated control model; introducing frequency adaptation into the integrated control model to obtain an integrated control model with frequency adaptability; and controlling the robot to perform follow-up motion using the integrated control model with frequency adaptability. The present invention considers how the robot can make corresponding adjustments to achieve frequency adaptation and achieve dynamic equilibrium with the participant's motion frequency under conditions of human-machine interactive motion collaboration, when the participant's motion frequency changes. Furthermore, this adaptation is long-term and stable, resulting in a better robot following effect.

This invention relates to the field of cognitive testing techniques and sensor-based measurement systems to create a block design test-based cognitive ability and psychomotor profile assessment system that can be used in various age groups. This system integrates testing media in the form of physical blocks, digital simulations, or a combination of both, as well as a rotation sensor-based data acquisition module to record the orientation and movement of the blocks in real-time during the assembly process. The obtained rotation data is then processed to analyze the level of accuracy, speed, interaction patterns, and movement coordination that represent the user's cognitive abilities and psychomotor profile. Unlike conventional methods that rely on subjective observations by the examiner, this system is capable of conducting assessments objectively, measurably, and based on quantitative data.Furthermore, this system enables more efficient testing by storing results digitally for monitoring, evaluation, and research. This invention is intended to support a variety of applications, from monitoring cognitive development in children, evaluating cognitive performance in adults, to early detection of cognitive and psychomotor decline in the elderly.

The invention discloses a dance kicking training device which comprises a C-opening bottom frame, lifting armrest frames installed on the left side and the right side of the top end of the C-opening bottom frame, and a double-column type vertical frame fixed to the position, between the two lifting armrest frames, of the top end of the C-opening bottom frame, and two shells of a mirror symmetry structure are installed on the outer wall of one side of the double-column type vertical frame. A rotating shaft is rotationally installed at the lower position in the shell, a foot-binding type rocker arm structure is installed at the end, close to the lifting armrest frames, of the rotating shaft, and protractors used for marking the swing angle of the foot-binding type rocker arm structure are installed on the outer walls, close to each other, of the two lifting armrest frames. The action coordination and the body control ability of the trainee are cultivated through an instant physical belt training feedback mechanism, so that the trainee can intuitively feel the force generation speed and angle change of the coach, and the training interactivity and the real-time feedback effect are enhanced.

The invention belongs to the technical field of glass lifter performance detection, and particularly relates to a frameless glass lifter performance detection system which comprises a test environment building module, a lifting test execution module, a data acquisition module, a motion coordination analysis module, a motion deviation analysis module and a performance evaluation module. Monitoring points are divided on the curved surface section at the upper end of the frameless glass according to the curvature, displacement data of each monitoring point are collected in multiple one-key lifting tests, acceleration, constant speed and deceleration time periods are divided according to the displacement data, motion imbalance is recognized through multi-point time difference comparison, and meanwhile the rotation angle of a driving arm is collected. The method establishes the mapping relation with the displacement of each monitoring point to carry out motion offset analysis, combines the motion imbalance and offset results, achieves the multi-dimensional and refined evaluation of the lifting performance of the frameless glass, and remarkably improves the detection precision, the abnormality recognition capability and the evaluation comprehensiveness.

The application discloses a kind of equipment and method for horizontal section and large inclination section water conduit maintenance operation, including center force bearing structure, support mechanism, tension applying mechanism, movement coordination mechanism and operation platform system, tension applying mechanism and movement coordination mechanism cooperate, make all support arm form a stable support system that can adapt to water conduit shape and posture.The application is modularized, lightweight design, and the support arm can be folded, so that the maintenance operation equipment can pass through the narrow entrance, and after being unfolded in the water conduit, a large-size, high-rigidity stable operation platform is formed, and the maintenance operation equipment can also move in the horizontal section and large inclination section of the water conduit, solving the problem of water conduit maintenance.

The present invention discloses a human behavior recognition method based on a motion cooperation space, comprising the steps of: S1, respectively performing key frame extraction on an initial bone sequence and a depth map sequence based on a motion state measurement coefficient; S2, for the bone sequence processed in step S1, extracting a motion cooperation space vector and splicing it into a motion cooperation space feature; for the depth map sequence processed in step S1, extracting DMM features to obtain a depth motion map; S3, simultaneously inputting the depth motion map and the motion cooperation space feature into a deep network for score fusion. Based on the idea of multimodal fusion, the present invention combines bone data and depth data to make the data more complete, realizes the complementarity of various heterogeneous information, eliminates the redundancy between modalities, and establishes a new behavior recognition method system, providing new ideas and theoretical basis for the research and application of human behavior recognition methods.

The invention relates to a deformable multi-legged robot, in particular to a deformable multi-legged robot for complex terrains, and belongs to the field of robotics, mechanical structures and bionic structures. In order to solve the problems that an existing ball leg composite motion robot is limited in autonomous obstacle avoidance capacity, unstable in mode switching posture, insufficient in motion collaboration and free of a response mechanism for ball leg damage, the robot comprises a robot body and six deformation walking mechanisms. The deformation walking mechanism comprises a hip joint structure, a double-leg connecting structure and two walking motion structures; the deformation walking mechanisms are evenly distributed on the robot body in the circumferential direction, the connecting ends of the six hip joint structures are evenly distributed and installed on the robot body in the circumferential direction, the robot body drives the six hip joint structures to rotate around the robot body in the axial direction, each hip joint structure is provided with one double-leg connecting structure, and the hip joint structures drive the double-leg connecting structures to rotate. The two walking motion structures are installed on the two-leg connecting structure, and each walking motion structure achieves inward or outward stretching motion.

The invention relates to the technical field of treatment instruments, in particular to rehabilitation training auxiliary equipment for an Alzheimer's disease patient, and solves the problems that most treatment devices need to be treated through a computer, the patient generally difficultly understands and uses the treatment devices, the training content is single, and multiple trainings cannot be performed at the same time. Four discharging mechanisms are arranged on the surface of the training table assembly. A medical worker guides a patient to take training pattern plates, the training pattern plates are arranged in a sudoku mode, then the medical worker guides the patient to remember the patterns of the four training pattern plates in each column, and then the patient takes four training plates with pattern grooves in corresponding shapes. The four training pattern plates are arranged according to the sequence of the patterns of the four training pattern plates in each column, so that medical staff can guide the patient whether the sorting is wrong or not, and the device not only exercises the memory and judgment ability of the patient, but also can exercise the exercise coordination ability of the patient.

1. Name of the product in this design: Robot Controller (Visual Control). 2. Purpose of this design: To control the robot's visual perception, movement, coordination of the actions of each axis, and to realize automated operation. 3. The key design feature of this product is its shape. 4. Images or photos that best illustrate the design key points: Use state diagrams.

The invention provides a manufacturing data classification analysis method and device based on a clustering algorithm and a medium, and the method comprises the steps: generating an original motion data set through collecting the bending angle value and rotation resistance of each knuckle and the time when a finger reaches a target position; according to the original motion data set, motion coordination abnormal data with the angle difference exceeding a threshold value and uneven rotation resistance display damping is identified, and an abnormal data subset is generated; according to the abnormal data subset, identifying measurement values of multi-finger motion coordination imbalance, and determining an imbalance measurement value combination; processing the imbalance measurement value combination through a clustering algorithm to generate a cooperative motion function group set; motion types are grouped according to the cooperative motion function group set, and an optimized group structure is generated; and outputting a manufacturing data classification analysis result according to the optimized group structure.

The invention discloses a human body lower limb movement cooperation feature description method based on multi-joint cooperation CPG, and belongs to the field of human body movement analysis and robot control, and the method comprises the steps: constructing a lower limb multi-speed gait movement data set, and building a human body lower limb kinematics simplified model in combination with Denavit-Hartenberg parameters; a corresponding coefficient angular component method is adopted to quantify the cooperative relationship between the joints, and the cooperative relationship between the joints is accurately described; building a multi-joint cooperative control CPG model based on cooperative characteristic driving according to the multi-joint chain connection characteristics of the lower limbs of the human body; the motion trails of the six joints of the lower limb serve as the input of a multi-joint cooperative control CPG model based on cooperative feature driving, and dynamic mapping between the cooperative features of the six joints of the lower limb and CPG parameters is achieved through adaptive Hopf-CPG network fitting learning. According to the invention, accurate description of human body lower limb joint movement cooperation features is realized.

This invention discloses a deep learning-based kinematic analysis system and method for the human sitting-to-standing process, belonging to the field of motion analysis technology. It solves the technical problems of high testing costs, low accuracy, and low stability in existing STS (Seated-to-Stand) motion testing technologies, which hinder the effective promotion of STS motion testing. Based on deep learning technology, this invention automatically tracks human joint nodes and achieves fully automated analysis of multi-dimensional, refined motion characteristics for various human movements from sitting to standing. It can comprehensively evaluate the range of motion, efficiency, stability, and coordination of human movement. Furthermore, this invention only requires video acquisition equipment to achieve comprehensive kinematic analysis of STS motion, solving the problems of expensive, space-consuming, and time-consuming motion capture systems using motion sensors and multi-camera motion capture systems with reflective markers. This significantly reduces the operational difficulty and testing cost of STS kinematic analysis.

1. The name of the design product: robot controller (drive control). 2. The use of the design product: for controlling the movement of robots, coordinating the actions of each axis, and realizing automated operations and other functions. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

This invention discloses a method and system for editing 3D assets based on dual representation and skeleton control. The method includes: acquiring dual representations of the same 3D asset; predicting the skeleton through a mesh and establishing skinning weight control relationships; defining the motion coordination relationship between the mesh and Gaussian points using face-point binding and affine transformation, supporting distance-aware weighted updates of Gaussian parameters; receiving user spatial constraint instructions; using the skeleton pose as the optimization variable; and performing gradient modulation optimization by combining geometric deviation loss and visual rationality regularization terms; finally, driving mesh deformation and synchronously updating the Gaussian representation, achieving semantically controllable, geometrically faithful, and rendering-efficient 3D asset editing. This invention constructs an affine binding coordination mechanism between mesh triangles and Gaussian points by fusing 3D mesh and 3D Gaussian splash dual representations, enabling high-quality interactive editing of 3D assets while maintaining geometric structural integrity and supporting semantically clear and rendering-consistent results.

This application belongs to the field of robot technology, and particularly relates to a robot door-opening method, device, computer-readable storage medium, and robot. The method determines a first movement radius of the robot's hand around the door axis, a second movement radius of the robot's waist around the door axis, and the body orientation adjustment angle required for the line connecting the centers of the robot's two feet to pass through the door axis; determines the planned trajectory of the robot's hand and the planned trajectory of the waist according to the first movement radius, the second movement radius, and a preset door-opening angle; and controls the robot to perform a door-opening operation according to the planned trajectory of the hand and the planned trajectory of the waist. Through the above method, the hand trajectory and the waist trajectory of the robot can be simultaneously planned according to the movement radius, and the robot is controlled to perform a door-opening operation according to the obtained planned trajectory of the hand and the planned trajectory of the waist, improving the movement coordination of the robot and achieving precise control of the whole-body movement of the robot.

The invention discloses a mechanical arm motion coordination optimization control method and system. The method comprises the steps that the difference between an initial target pose and an expected target pose of a mechanical arm is determined based on the initial target pose and the expected target pose, and a pose error vector is obtained; a vector error of the mechanical arm is determined based on the pose error vector, and a control matrix of the mechanical arm is determined based on the vector error; simulation control is conducted on the operation parameters of the mechanical arm on the basis of the control matrix, and pose error characteristics of the mechanical arm after the simulation control is finished are determined; the pose error state of the mechanical arm is analyzed and evaluated based on the pose error features, and a pose error state evaluation value is obtained; and determining an optimization coefficient matrix based on the pose error state evaluation value, and optimizing the control matrix to obtain an optimized motion control matrix. By establishing the control matrix and conducting pre-simulation and quantitative evaluation, potential motion performance bottlenecks can be observed in advance, dynamic optimization is conducted through the data-driven self-adaptive optimization coefficient matrix, the flexibility and accuracy of the mechanical arm are improved, and it is ensured that the motion process is stable.

The application discloses a kind of seven-axis engraving robot joint shaft and synchronous monitoring method of rotary table, it is related to industrial robot technical field, comprising: when the numerical control system is started, run system macro file to carry out dynamic detection, ensure that rotary table and joint shaft are in task before movement coordination consistent.In the dynamic detection process, when the cutter approaches rotary table, the relative position of cutter and rotary table is detected in real time by sensor, and the data is transmitted to control system, and the cutter speed is dynamically adjusted according to the feedback data, to ensure that the rotary table slot is approached with smooth speed.Judge whether the cutter is accurately placed in the slot: if it is accurately placed and no collision occurs, it is determined that the rotary table and joint shaft are synchronous;Otherwise, it is determined that the rotary table and joint shaft are not synchronous and trigger system alarm, record error log and prompt operator to repair.Through dynamic detection and real-time adjustment of cutter speed, ensure that the joint shaft and rotary table movement is synchronous, improve processing accuracy and operation stability, while reducing equipment wear and tear and improving operation safety.

The invention belongs to an underwater robot control and decision-making technical scheme, and particularly relates to a multi-underwater robot formation control and decision-making method for seabed detection. A step of establishing a leader-follower system with a dynamic hierarchical relationship, including a step of implementing stable path tracking on a set detection path for a leader underwater robot of the constructed system by adopting an improved path tracking guide method based on a PID principle; a kinematics-based state prediction-tracking architecture is adopted for the formation of the follower underwater robots of the constructed system; in the face of comb-shaped detection path steering, the leader underwater robot and the follower underwater robot adopt an equivalent travel-based formation steering conversion decision strategy; the multi-degree-of-freedom control scheme of the underwater robot is realized by adopting an integral S-plane controller for the motion control of the underwater robot of the leader and the follower of the system. The method is used for solving the problems of formation keeping, path tracking and motion coordination under the underwater acoustic weak communication condition.

The present application discloses a robot multimodal perception and motion coordination control method and device. The robot method includes: obtaining multiple types of sensor information as multimodal perception data according to a preset cycle through multiple types of sensors arranged in the robot operation area, and the multimodal perception data includes laser radar data, infrared sensor data and visual sensor data. A conveying device is provided in the robot operation area; based on the multimodal perception data, analyzing the transmission parameters of the conveyor belt of the conveying device and the cargo parameters of the goods on the conveyor belt; dynamically adjusting the historical motion parameters of the robot's mechanical arm according to the transmission parameters and the cargo parameters to obtain the optimal motion coordination parameters suitable for the conveying device; constructing and executing the motion control instructions corresponding to the optimal motion coordination parameters to operate the goods on the conveyor belt. Therefore, the use of the embodiments of the present application can improve sorting efficiency, reduce maintenance costs, and ensure the stability of the entire production process.

The invention relates to a multi-mechanical-arm cooperative control method based on multi-source time delay compensation cooperative optimization, and belongs to the field of automation and robot cooperative control. The method comprises the following steps: establishing a collaborative error dynamic model fused with a multi-source time delay compensation item offline, and designing a collaborative optimization objective function comprising a synchronization error, control energy consumption and a time delay compensation effect evaluation factor; and multi-source time lag identification is periodically performed during online operation, an optimization function is solved based on a distributed model prediction control framework, and a control instruction of each mechanical arm is generated. The time delay compensation problem is deeply embedded into the optimization process of cooperative control, and unified active management and global performance optimization of multi-source time delay of sensing, communication, calculation and the like are achieved. The synchronous precision and the motion coordination of the multiple mechanical arms in the environment with time varying and uncertain time delay are remarkably improved, the robustness of the system to sudden large time delay is enhanced, the rapid self-adaptive capacity is achieved, and the reliability and the overall performance of collaborative operation of the multiple mechanical arms in a complex industrial scene are greatly improved.

A computer-assisted medical system includes a robotic manipulator arm configured to support an instrument. The instrument includes an instrument axis and jaws disposed at a distal end of the instrument axis. The computer-assisted medical system also includes a controller coupled to the manipulator arm. The controller includes a computer processor and is configured to track movement of the instrument along an insertion axis of the instrument and coordinate the size of a jaw aperture defined by the jaws with the movement of the instrument along the insertion axis to achieve a target aperture.

The invention discloses a multi-view visual inspection machine, which is characterized in that (1) a single lens is used for high-efficiency coverage: a product inspection platform (rotating around a vertical center line and moving left and right), a visual inspection camera (swinging left and right around a horizontal center line extending front and back and moving front and back) and a camera (moving up and down) are cooperated in multi-dimensional movement; 360-degree omnibearing shooting can be realized only by a single lens (namely the lens of the camera), and compared with the traditional multi-camera layout, the hardware cost is greatly reduced, the equipment volume is reduced, and the space utilization rate is improved. And (2) the detection adaptability is stronger: the lens (namely the lens of the camera) can rotate by 90 degrees and move up and down / back and forth, the product detection platform can rotate by 360 degrees and move left and right, the detection requirements of irregular-shaped parts such as springs and hardware can be flexibly met, and details of each part can be accurately captured no matter whether the parts are symmetrical or not and have complex curved surfaces or not. And (3) the detection efficiency is improved: a single lens does not need to switch positions.

The invention relates to the technical field of robot control, in particular to a self-adaptive control method and system for an upper limb rehabilitation robot. Comprising the steps that motion data of upper limb joints of a patient are collected through a sensor array and fused to generate comprehensive motion vector representation, motion pattern classification is conducted through a classification model, and whether coordination deviation exists between the joints or not is judged; if deviation exists, joint deviation distribution information is obtained, robot control parameters are optimized through an optimization model, and an adjustment instruction sequence is generated to drive a robot actuator to conduct intervention; after intervention, the intervention effect is evaluated through feedback data, the personalized demand model is updated according to the effect, and a subsequent intervention scheme is optimized. According to the invention, the defects of an existing rehabilitation robot in coping with the complex motion coordination problem are overcome, the self-adaptive control based on real-time data and feedback is realized, and the rehabilitation treatment effect and the personalized level are remarkably improved.