98 results about "Motion generation" patented technology

The invention provides a road detection vehicle pavement disease detection method and system based on multi-sensor fusion, and relates to the technical field of road engineering detection, and the method comprises the steps: 1, configuring at least one two-dimensional image collection unit and at least one three-dimensional image collection unit on a detection vehicle to obtain a configuration result; 2, according to the configuration result, in the driving process of the detection vehicle, a geometric reference area used for multi-source data space alignment is established based on lane marking lines in a to-be-detected road surface area; and step 3, performing structured division on the geometric reference area to obtain regularly distributed detection areas, and calculating spatial geometric feature changes generated by vehicle composite motion in the detection areas based on distribution features of the detection areas in combination with translational motion and rotary composite motion states existing in the driving process of the detection vehicle so as to obtain the spatial geometric feature changes of the detection areas. And obtaining a rigid body space composite kinematics characteristic resolving result of the detection area. According to the invention, efficient, accurate and full-dimensional detection of pavement diseases is realized.

The invention discloses a text-to-action generation method and system based on body part fine-grained representation, and belongs to the field of human body action generation. Body part-level fine-grained discretization modeling is performed on human body actions to obtain an action encoder and an action decoder which can stably reconstruct a continuous action sequence; the method comprises the following steps: taking a part fine-grained discrete action space as a producible space, introducing video potential representation as space-time dynamic priori, establishing an alignment modeling mechanism of the video potential representation and the action discrete space, and training to obtain a conditional generation network, so as to realize stable prediction and iterative completion of an action discrete index sequence in a reasoning stage; and a continuous human body action sequence is reconstructed through an action decoder, and finally a human body action sequence which is consistent with text semantics, richer in details and more coherent in time sequence is generated. According to the method, the technical threshold and data dependence of action content production can be reduced, and the controllability and generalization ability of action generation are improved.

The invention discloses an unmanned aerial vehicle multi-mode fusion radio positioning and signal identification method and system, and relates to the technical field of radio positioning and detection.The method comprises the steps that an airspace radio environment is continuously monitored in a monitoring area through all receiving stations, a power spectrum sequence and an unmanned aerial vehicle communication signal are obtained, and spectrum features are extracted from the power spectrum sequence; for the same launch event, acquiring a three-dimensional motion track of the unmanned aerial vehicle according to the arrival time of each receiving station; echo signals generated by unmanned aerial vehicle rotor wing and vehicle body movement are obtained through a radar, and micro-Doppler features are extracted from the echo signals; acquiring protocol related modulation features, cyclic spectrum features and protocol features according to the unmanned aerial vehicle communication signals; performing multi-modal feature fusion on the spectrum feature, the micro-Doppler feature, the modulation feature, the cyclic spectrum feature and the protocol feature to obtain a deep joint feature; identifying the type of the unmanned aerial vehicle according to the deep joint feature, and obtaining a type label; and constructing an unmanned aerial vehicle feature signature by using the category label, the three-dimensional motion trail and the depth joint feature. According to the invention, the accuracy, robustness and supervision capability of unmanned aerial vehicle positioning and signal detection in a complex environment can be improved.

A system is provided that stabilizes an applicator in response to the motion caused by a user. The system includes a motion stabilizer; and an adapter that holds a cosmetic applicator. The motion stabilizer includes a receiver configured to be coupled with the adapter, at least one sensor configured to detect a movement caused by a user, circuitry configured to determine a compensation movement to offset the detected movement; and at least one motion generation device embedded in the receiver configured to control a motion of the cosmetic applicator according to the determined compensation movement, wherein the adapter includes circuitry that is configured to transmit an identifier to the receiver, the identifier indicating a type of the cosmetic applicator, and the motion generation device is configured to set at least one parameter for controlling the motion of the cosmetic applicator according to the type of the cosmetic applicator.

The invention discloses a method for simulating particle transport and related equipment, and relates to the technical field of radiotherapy, and the method comprises the steps: constructing an equivalent density model along a particle transport direction based on the structure parameters of an energy regulator combination, and building a matched boundary information table, the boundary information table at least records the position information of the downstream boundary of each energy regulator piece in the energy regulator combination, the equivalent water thickness accumulated from the incident end to the boundary, and the air gap length between the boundary and the upstream boundary of the next energy regulator piece; obtaining a particle current position and boundary information table; the medium area where the current free path of the particles is located is judged, and differential calculation is carried out on offset generated by movement of the particles in different areas according to the medium area until the particles pass through the energy regulator combination to be transported; according to the method, rapid and accurate judgment and differential offset calculation of the boundary are realized, so that the boundary processing complexity is remarkably reduced and the calculation efficiency is improved on the premise of ensuring the physical simulation precision when the particles pass through the energy regulator.

The invention belongs to the technical field of mechanical arm automation control, and discloses a mechanical arm teleoperation system based on multi-scale feature fusion and an action generation method, the mechanical arm teleoperation system comprises a teaching arm, a learning arm, a signal acquisition module and a processor; a multi-scale feature extraction and adaptive feature fusion module and an action generation module are arranged in the processor; the signal acquisition module comprises a first camera and a second camera; the learning arm comprises a first base, a first joint, a second joint, a third joint and a fourth joint, the first joint, the second joint, the third joint and the fourth joint are arranged on the first base and sequentially connected, a clamping jaw and a support are fixed to the fourth joint, a camera is arranged on the support, and the teaching arm comprises a second base fixedly connected with the working face. A fifth joint, a sixth joint, a seventh joint and an eighth joint which are connected in sequence are arranged on the second base; a handle body and a control trigger are arranged at the end, away from the seventh joint, of the eighth joint. The invention provides the master-slave teleoperation physical platform with a compact structure.

This invention belongs to the field of vibration control technology and discloses a viscous damper for controlling vertical vibration. The viscous damper adopts a double-cylinder, unsealed structure. The two cylinders are connected by a connecting rod hole in the middle of the cylinder partition. One end of the connecting rod is rigidly connected to a piston inside the second cylinder, and the other end passes through the cylinder partition and the top plate of the first cylinder before connecting to a structure. The bottom of the second cylinder is connected to another structure. When the two structures generate a vertical relative velocity, the connecting rod drives the piston to move in the damping fluid of the second cylinder, generating viscous resistance and suppressing the relative motion of the two structures. This invention does not require strict sealing, has a simple structure, low manufacturing cost, and better durability. The damping coefficient can be dynamically adjusted as needed by the comb teeth or the gradually changing inner cavity of the cylinder, resulting in higher efficiency compared to traditional dampers. This invention can effectively control the vertical or slightly inclined relative motion between various large structures such as bridges, cables, building internal structures, and marine engineering projects caused by various dynamic loads.

The invention discloses an industrial robot and environment contact event identification method based on cross-modal learning, and the method comprises the steps: collecting a visual image and a force sense time sequence of the tail end of a robot, and extracting visual features and force sense features through convolution operation and continuous wavelet transformation; a force sense feature driving offset generation network is utilized to calculate a time offset scalar, time dimension deformable convolution is executed on visual features, and time-space accurate alignment of visual and tactile features is achieved; according to kinematics parameters of the robot, kinetic theoretical stress is calculated, a physical residual vector is obtained through difference between the kinetic theoretical stress and actually-measured force, and inertia force interference generated by motion of the robot is eliminated; mapping the physical residual error, fusing the mapped physical residual error with the aligned visual tactile features, and inputting the fused physical residual error into a neural network to identify a contact type; according to the method, a physical consistency constraint and anti-occlusion reconstruction mechanism is introduced in a model training stage, so that the problems that multi-modal data are asynchronous, and the model lacks physical interpretability and visual occlusion are effectively solved, and the accuracy and robustness of event recognition are improved.

Multiple motion parameters are determined from the simulated object mesh. These motion parameters include information on the virtual character's motion velocity, the object's deformation rate, and the object's deformation region size. Based on the first audio parameter control and the multiple motion parameters, a friction sound is retrieved from a friction audio database containing multiple sample friction sounds. The first audio parameter control is configured to control the characteristics of the friction sound. Based on the second audio parameter control and the multiple motion parameters, a crumpling sound is retrieved from a crumpling audio database containing multiple sample crumpling sounds. The second audio parameter control is configured to control the characteristics of the crumpling sound.

A motion generation device is configured to generate motion of a slide of a press device including the slide to which an upper die is attached, a bolster on which a lower die is placed, and a servomotor configured to move the slide reciprocally in the up and down direction. The motion generation device includes a motion generation section. The motion generation section is configured to generate a derivative motion of the slide at a cycle time different from the cycle time of the standard motion of the slide, such that the derivative motion includes the same motion as a first region of the standard motion including at least from top dead center to the end position of the molding region, and the speed of the slide at top dead center of the derivative motion is the same as the speed of the standard motion.

The invention discloses a mechanical arm action generation method based on a self-supervised reconstruction task. And training a mechanical arm imitation learning strategy close to an expert strategy on the basis of the obtained expert motion trail for manually controlling the mechanical arm to complete the specified task. According to the mechanical arm imitation learning strategy, a de-noising diffusion probability model with U-Net as a backbone network is used, down-sampling and up-sampling coding is carried out on an action sequence after Gaussian noise is randomly added, a global condition vector is used in each coding layer to modulate features, the action increment is predicted, the control action of a mechanical arm is output, and the control action of the mechanical arm is obtained. And executing and completing the specified task. In the training process, a self-supervised reconstruction task is introduced, and the difference between the action based on middle-layer feature reconstruction, point cloud features and expert motion trails is compared, so that a denoising network is promoted to carry stronger observation semantics, the characterization ability of a model to a three-dimensional hidden space is enhanced, and the success rate and generalization ability of task execution of the mechanical arm are effectively improved.

This invention provides a laser cutting machine and its vibration reduction method, relating to the field of laser cutting. The solution includes a machine bed with a gantry movable in the X-direction, and a cutting component movable in the Y-direction on the gantry. It also includes: a counterweight, movable in the X-direction within the machine bed, capable of moving synchronously with the gantry; a drive assembly, mounted on the machine bed, driving the counterweight; and a controller electrically connected to both the gantry's drive motor and the drive assembly. The controller can acquire the gantry's motion parameters in real time and calculate the counterweight's X-direction motion parameters, ensuring that the counter-inertial force generated by the counterweight's X-direction movement is equal in magnitude and opposite in direction to the impact force generated by the gantry's movement. This invention reduces the impact of processing vibration on processing quality and equipment lifespan.

System for determining the amount of pressure applied to a brush head (12) and for providing feedback to a user as soon as a measured pressure reaches a predetermined threshold, the system comprising: a brush head (12); a drive unit (14) connected to the brush head (12), wherein the drive unit (14) has a drive shaft (42) which is activated to move the brush head (12) relative to the drive shaft (42); a magnet (60) which moves in a repeating manner as a function of the movement of the drive shaft (42); a Hall effect sensor (62) which generates a signal based on the movement of the magnet (60); a feedback device; and a microprocessor (64) connected to the Hall effect sensor (62) and the feedback device, wherein the microprocessor (64) is programmed to activate the feedback device as a function of the change in the speed of movement of the magnet (60), wherein the movement of the drive shaft (42) is a rotational movement, wherein the movement of the drive shaft (42) is an oscillating rotational movement about an axis, and wherein the microprocessor (64) generates a signal based on the change in the rotational speed of the drive shaft (42).

The present invention relates to a device and method for generating context-aware motion using text and emotion embeddings. An electronic device according to one embodiment of the present invention includes a memory and a processor connected to the memory, and the processor receives input information including a text prompt instructing the content of a character's action and emotion information to be assigned to the action for generating three-dimensional motion from a user terminal, and vectorizes the received text prompt and the emotion information, respectively, to generate a text embedding for the content of the action and an emotion embedding that determines the nuance of the action, and generates a motion sequence based on the text embedding using a Generative AI model, but reflects the emotion embedding as a condition of the generation process to assign an emotional context to the character's action, and can generate the motion sequence with the assigned emotional context as final motion data.

The invention provides a slow action generation method based on motion focus area analysis. The method comprises the following steps: determining a video of a slow action to be generated; detecting a motion focus area in the video, and grading the motion focus area; and for different grades of motion focus areas, different strategies are adopted to carry out motion modeling and differential interpolation processing, and a slow motion frame sequence is generated. According to the invention, through identification and grading processing of the motion focus area, high-precision calculation of the core motion object, simplified calculation of the secondary area and simplest processing of the static background, compared with a traditional scheme of uniform and dense calculation of the whole frame, the method has the advantages of high calculation complexity and lower calculation amount, and guarantees the visual effect of the core area.

This invention provides a method and system for generating digital human body movements based on a deep learning model, comprising: acquiring deep learning information and audio / video data; separating and processing the audio / video data, and obtaining body movement classification data and text data based on the deep learning information; establishing a tuple that associates text with corresponding body movement tags and storing it in a database; when the digital human broadcasts, determining whether a body movement tag corresponding to the text can be found in the database; if so, using the body movement tag to drive the digital human to display the corresponding body movement; if not, associating the text with the corresponding body movement tag in the tuple based on semantic similarity, driving the digital human to display the corresponding body movement, and updating the database. This invention can adaptively guide the generation of digital human body movements through a deep learning model and automatically improve the recognition effect.

A motion generation apparatus (1000); (2000) for a motion platform system has a plurality of motion control arrangements (1201), (1202), (1203) that include control members (1211), (1212), (1213) and couplings (1241), (1242), (1243) configured to engage respective inclined portions (1251), (1252), (1253) of the control members. Laterally driving the or each respective control member forces the or each respective coupling in a direction along an inclined path P1, P2, P3 to impart a vertical force to a portion (1801), (1802), (1803) of a motion platform (1800). Motion and positioning of the platform (1800) is determined by the combined movement and / or positioning of the control members (1211), (1212), (1213).

In the control of a work machine, contact with other work machines is avoided while reducing work efficiency reduction caused by avoidance to a minimum. There are: an action management unit (211) that acquires a work instruction (230) including a final target position and a present position of the work machine (100) and sets a target position; a path planning unit (212) that generates a target path (240) between the present position and the target position; and a motion generation unit (213) that causes the work machine (100) to travel along the target path (240), and the action management unit (211) decides an avoidance position from an avoidable position based on a work range of another work machine different from the work machine (100) and at least one of the present position of the work machine (100) and the final target position, and sets it as the target position when receiving an avoidance instruction (250) containing the avoidable position based on the work range of the other work machine.

The application discloses a kind of capacitive displacement sensor calibration device and method, belong to metrological testing technical field, comprising: host computer is started linear displacement table by controller module and carries out the linear motion required in calibration work, multiple degrees of freedom error and displacement value generated by linear motion are measured simultaneously using optical measurement module, and are transmitted to host computer by data acquisition module, host computer is adjusted by controller module and is located in the multiple degrees of freedom microstage pose of linear displacement table bottom to compensate multiple degrees of freedom error in linear motion, realizes to capacitive displacement sensor calibration.The application effectively breaks through the bottleneck that traditional capacitive displacement sensor calibration technique precision is limited, measurement and compensation function are integrated, eliminate multiple degrees of freedom error coupling influence, can satisfy the calibration demand of high-precision capacitive displacement sensor.

Such a fuel filler flap arrangement with a fuel filler flap that is mounted on an articulated arm in a limited manner and which is pivotally mounted relative to a vehicle-side filling area, wherein a mechanical positive control engages the fuel filler flap, which has at least one flexible tension member that is articulated in the area of ​​a joint axis of the articulated arm on the one hand and on the fuel filler flap on the other hand, in order to generate a relative movement of the fuel filler flap relative to the articulated arm depending on a pivoting movement of the articulated arm about the joint axis, is known. According to the invention, the articulated arm is designed as a hollow profile with an internal closed channel penetrating the articulated arm lengthwise, and the at least one tension member is routed through the channel. Use for passenger cars

The invention discloses a non-linear rigidity automatic adjusting vibration isolation device and a control method. The device comprises a base, a supporting seat, a positive rigidity mechanism, a negative rigidity mechanism and a dynamic adjusting assembly. The negative stiffness mechanism adopts the design of three layers of uniformly distributed'connecting rod-tension spring 'transmission units, generates negative stiffness by converting vertical displacement of a supporting seat into horizontal movement of a tension spring, and is connected with positive stiffness provided by the positive stiffness mechanism in parallel to form a quasi-zero stiffness core mechanics framework. The dynamic adjusting assembly can accurately adjust the working height of the positive stiffness mechanism, and in combination with a feedback control system with an angle sensor as the core, self-adaptive adjustment of the balance position of the system under different loads and maintenance of the quasi-zero stiffness state are achieved. The positive stiffness mechanism is integrated with a magneto-rheological damper, and the damping force of the magneto-rheological damper can be subjected to real-time and intelligent adjustment through a feedforward-feedback composite control strategy based on multi-sensor information fusion so as to suppress resonance, impact and broadband vibration. The problems that in the prior art, the vibration isolation frequency band is narrow, load self-adaption cannot be achieved, damping adjustment is not intelligent and the like are solved, and high bearing, strong vibration reduction and full-working-condition self-adaption vibration isolation are achieved.

The embodiment of the invention discloses a voice-driven virtual character action generation method. A specific embodiment of the method comprises the following steps: in response to a received audio signal, performing cross-modal feature extraction processing on the audio signal to obtain a cross-modal feature set; according to the cross-modal feature set and the motion primitive codebook, generating combined motion feature representation; performing style feature extraction on the audio feature set to obtain a style feature set, and generating a normalized parameter set according to the style feature set; performing temperature concentrated weight re-calibration on the combined motion feature representation to obtain a calibrated combined motion feature representation; according to the normalized parameter set, style self-adaptive adjustment is carried out on the calibrated combined motion feature representation, and a final motion sequence is obtained; and inputting the final action sequence into an associated server to drive the virtual character to execute a corresponding action. According to the embodiment, the accuracy of virtual character action generation can be improved, and the response time can be shortened.

To prevent the control device from exceeding its allowable computational load and to suppress a decrease in control accuracy. [Solution] The drive control device includes: an motion generation unit that generates a target motion of the front work device using parameters based on the detection result of the attitude sensor and work design information; an actuator control unit that calculates the target operating speed of the actuator based on the target motion generated by the motion generation unit and generates and outputs a control signal to control the operation of the actuator at the calculated target operating speed; a computation load estimation unit that estimates the computation load of the drive control device based on the calculation time of the target motion in the motion generation unit, the calculation time of the target operating speed in the actuator control unit, and the load of the overall control device; and a parameter adjustment unit that adjusts the parameters to reduce the computation load of the motion generation unit if it is determined that the computation load estimated by the computation load estimation unit is higher than a predetermined reference value.

This invention provides a method for online force assessment of characters in a virtual reality environment, aiming to achieve real-time quantitative assessment, physical accuracy, and high robustness of force on humanoid character movements in virtual reality environments. This method combines a motion generation model and a physics optimizer, using an end-to-end integrated approach to dynamically estimate key mechanical parameters such as joint torque and ground reaction force. Specific steps include: acquiring user motion trajectory data from sparse sensors (such as VR headsets and controllers); generating preliminary full-body motion postures using a motion generation model based on discrete latent space learning; performing physical correction and force estimation on the motion using a physics optimization module (employing a dual proportional-differential controller and a motion tracking optimizer); integrating motion data and force parameters; and outputting character animation and force visualization results in real time through a rendering engine. Through the collaborative design of motion generation and physical force assessment, this invention significantly improves the realism, real-time performance, and adaptability of virtual character movements, making it suitable for VR applications such as security monitoring, medical training, and sports simulation, enhancing immersion and interaction efficiency.

To provide a gaming machine that can give a sense of speed to the movement of movable parts. [Solution] The system includes a liquid crystal display device 41 and a movable mechanism device 43. When the movable mechanism device 43 moves in a predetermined direction (downward in the illustration), the liquid crystal display device 41 displays an effect EF6 related to the shape of the movable mechanism device 43 in the predetermined direction (downward in the illustration) prior to the movement of the movable mechanism device 43. Furthermore, the expected value of generating a game state advantageous to the player is higher when the effect EF6 or the movable mechanism device 43 moves to near the center of the liquid crystal display device 41 compared to when it does not move to near the center of the liquid crystal display device 41 (see Figure 19(b)).

The application provides a fixed offshore wind turbine system underwater shaking table hybrid test method and system considering multi-field coupling, which can be used in the technical field of structure test. The fixed offshore wind turbine system underwater shaking table hybrid test method considering multi-field coupling comprises the following steps: inputting a test load and a horizontal inertia mass into a numerical substructure model for dynamic calculation, and outputting a first acceleration of a tower top; in the case that a test seismic wave is applied to the offshore wind turbine model through an underwater shaking table and a test wave flow load is applied through a wave and current generating device, determining a displacement stroke according to a difference between a second acceleration generated by a shaking table surface of the underwater shaking table and the first acceleration; and based on the displacement stroke, controlling horizontal movement of a mass block, so as to superimpose an inertial force generated by the mass block movement on the tower to apply a fluctuating wind load in the case that an average wind load in a test wind load is applied to the tower through a counterweight block loading device.

This invention discloses a stylized human motion generation method based on spatiotemporal attention, comprising the following steps: using a publicly available human motion style dataset, preprocessing it, and then dividing it into training and testing sets; constructing a stylized motion generation network model based on spatiotemporal attention; training the stylized motion generation network model based on spatiotemporal attention using the training set and updating its parameters; using the trained human motion generation model, taking the original motion content sequence and target style information as input, and outputting a stylized human motion sequence that retains the original action semantics and possesses the target style characteristics. This invention overcomes the problems of style mean-averaging and loss of fine-grained dynamics caused by temporal averaging aggregation in existing technologies, as well as the lack of adaptive attention to key spatiotemporal positions. It achieves fine modeling of multi-scale, non-uniformly distributed style cues, thereby generating human motion sequences with distinct styles, rich details, and well-preserved semantic structure.

The embodiments present a system and method for generating motion of a 3D character using rotation range constraints based on joint-specific biomechanical information based on artificial intelligence. A method according to one embodiment receives a text prompt for generating motion of a 3D character from a user terminal, inputs the text prompt into a text encoder to generate a text condition vector, obtains skeleton configuration parameters including a character type, an active joint set, and a character proportional parameter based on the text condition vector, generates skeleton structure information including joint list information, joint connection information, joint characteristic information, and joint rotation axis information based on the skeleton configuration parameters, inputs the character proportional parameter and the skeleton structure information into a biomechanics encoder to generate a biomechanics context vector including an allowable rotation range per joint, a joint type, and a bone length, inputs the text condition vector and the biomechanics context vector into a diffusion-based motion generation model to generate a rotation sequence per joint, transmits 3D motion data generated by applying the rotation sequence per joint to the user terminal, and performs scale adjustment and shift adjustment on the output feature vector generated in the graph transformer layer of the diffusion-based motion generation model using the biomechanics context vector.

The utility model discloses a kind of walking welding robots, including platform, platform one end is connected with stand, the other end is connected with diagonal brace, first guide mechanism is installed in platform, first sliding table is installed in first guide mechanism, first drive mechanism is connected with first sliding table, second guide mechanism is installed in first sliding table, second drive mechanism is installed in first sliding table, second sliding table is installed in second guide mechanism, and is connected with second drive mechanism, manipulator is installed in second sliding table, and welding torch is connected in manipulator.Platform is extended from the upper side of stand to the side of stand and forms overhanging structure, and positioning of platform is strengthened by diagonal brace, and larger movement space is left for the box to be welded, interference with the movement of box is avoided, and manipulator and welding torch with two degrees of freedom are hoisted by platform, can be welded to box at different angles and directions, compared with artificial welding, greatly improve welding precision and welding efficiency.

The application provides a multi-stage semantic emotion-driven digital human action generation method, and relates to the technical field of digital human action generation. The application extracts audio features and text semantic features and completes time alignment and fusion through multi-modal preprocessing of input audio and text to obtain a multi-modal feature sequence. Then, the sequence is used to identify semantic intent and analyze emotion to obtain a semantic intent sequence and an emotion curve containing categories, intensity and change trend. Subsequently, a global action script containing action type, intensity, duration and priority is generated according to a preset action mapping rule. The script is encoded into a feature vector and input into a lightweight neural network to obtain an action parameter sequence containing facial expressions, mouth shapes, skeletal actions and gaze directions. After time sequence smoothing and physical constraint checking, the final digital human driving parameters are output, which can realize low-power real-time operation, smooth action, accurate mouth shape synchronization and emotion and semantic matching.