33 results about "Simulated reality" patented technology

In various examples, a language model may be trained and used as part of an interface for a simulation system. For instance, user inputs may be applied to the language model and the language model may be trained to generate code, make API calls, or perform any other operations to interact with and / or control various aspects of the simulation. In some examples, the language model may generate code for, among other things, creating and / or customizing a virtual environment associated with the simulation. For instance, the generated code may include, but is not limited to, code for rendering the virtual environment, code for rendering and simulating behaviors of virtual agents (e.g., pedestrians, vehicles, animals, etc.) and / or any other objects (e.g., road signs, buildings, trees, etc.) within the virtual environment, code for recreating and simulating real-world events from recorded sensor data, etc.

The invention provides an autonomous parking method and system based on end-to-end reinforcement learning, a medium and equipment. The method comprises the following steps: acquiring an image of a real scene, laser point cloud information and inertial measurement unit data; constructing a scene model according to the real scene image, the laser point cloud information and the inertial measurement unit data; under the scene model, inputting the rendered look-around image into a preset end-to-end reinforcement learning network, setting a preset auxiliary task, guiding the preset end-to-end reinforcement learning network to train by adopting a progressive guide reduction strategy and a soft prediction collision penalty mechanism, and determining a trained end-to-end reinforcement learning network model; and inputting the real look-around image information of the target vehicle into the trained end-to-end reinforcement learning network model, and determining a parking prediction trajectory of the target vehicle. According to the method and the device, an end-to-end reinforcement learning mode is adopted, error accumulation is reduced, the parking precision and the parking capability upper limit are improved, and reality-simulation-reality scene seamless migration is realized.

The invention relates to the technical field of data expansion, in particular to a malicious prompt data set expansion method based on Mongolian. According to the method, high-frequency roots and affixes in a Mongolian basic malicious prompt corpus and a universal corpus are extracted, morphological analysis is combined, targeted malicious prompt samples can be constructed, the diversity and authenticity of a Mongolian safety evaluation data set are enhanced, candidate malicious prompt samples are optimized by adopting a genetic algorithm, and the safety evaluation accuracy of the Mongolian safety evaluation data set is improved. According to the method, the expansion sample is enabled to better conform to syntax and semantic rules of the Mongolian, effectiveness of the attack sample in the Mongolian scene is ensured, the expansion data set is enhanced by using the antagonism generation strategy, robustness and antagonism of the data set are improved, attack behaviors possibly occurring in a real scene can be simulated, and the robustness and the antagonism of the data set are improved. Therefore, an effective sample generation tool is provided for safety evaluation in a Mongolian scene, and the anti-attack capability of the Mongolian model is improved.

The invention relates to the technical field of automatic driving, and discloses a mixed reality automatic driving algorithm simulation method for pedestrian safety, and the method comprises the steps: S10, analyzing a road data file based on a simulation engine to obtain road data, and constructing a simulation scene through the road data; s20, placing the automatic driving vehicle model and a virtual substitute in the simulation scene, and obtaining dynamic behavior simulation data based on the simulation engine; s30, embedding a to-be-tested automatic driving algorithm into the simulation engine, and simulating a traffic flow in a real road condition scene; s40, the behavior information of a real pedestrian is mapped to the virtual substitute through a sensor, and a simulation data set generated by the interaction behavior of the virtual substitute and the traffic flow is acquired; and S50, storing the simulation data set through a database, analyzing and processing the simulation data set by adopting a data analysis algorithm, and generating a simulation test result based on the analyzed and processed simulation data set.

An innovative augmented reality / virtual reality (AR / VR) crossbow system that includes a bow frame assembly, a stock, a sight assembly, a cocking assembly, a resistance assembly and an electronic device assembly with a mobile device. These components are configured to structurally interact to provide the user with an experience of loading, aiming and firing a virtual crossbow arrow that closely simulates real-life archery and crossbow scenarios without firing an actual crossbow arrow. Due to its unique components and their layout, the AR / VR crossbow system is not configured to fire real arrows. An interactive crossbow application is loaded on the mobile device and simulate real life archery scenarios such as hunting scenarios or target competition scenarios. The mobile device also includes a gyroscope to analyze the orientation of the crossbow frame assembly and a microphone to determine when a simulated arrow is fired within the crossbow application.

In one implementation, a non-transitory computer-readable storage medium stores program instructions computer-executable on one or more processors of an electronic device to perform operations. The operations include presenting, on a display of the electronic device, a simulated reality (SR) environment at a first immersion level, where the first immersion level is associated with a first location of a reality boundary. Using a rotatable input device of the electronic device, input is received representing a request to change the first immersion level to a second immersion level. In accordance with receiving the input, the SR environment is presented at the second immersion level, where the second immersion level is associated with a second location of the reality boundary.

The present application relates to the technical field of graphic simulation system, specifically to a hydraulic fracturing process simulation and optimization system based on digital twin technology; containing real-time input, probabilistic simulation, adaptive assimilation and risk analysis and control unit; the system generates prior fracture probability cloud by combining agent model with real-time data; the core is to generate posterior fracture probability cloud by assimilating monitoring data, and to calculate simulation-realistic credibility index and probabilistic risk boundary accordingly; the system generates adaptive control signals according to the index and feeds back to the assimilation unit; the present application overcomes the false accuracy of traditional deterministic simulation, and realizes the quantification and intuitive display of fracture uncertainty.

The utility model discloses a limited space operation and rescue drilling platform, which belongs to the technical field of drilling platforms, and comprises a platform main body and a simulation pipeline assembly arranged at the bottom of the platform main body, the top of the platform main body is provided with a main well mouth and side well mouths positioned on two sides of the main well mouth; the simulation pipeline assembly comprises a main well pipe, a side well pipe, a transverse well pipe and a maintenance bin, the main well pipe, the side well pipe and the transverse well pipe are the same in structure and each comprise two same semicircular pipes, and the semicircular pipe located on the front face is a transparent pipe. Through the arrangement of the platform main body and the simulation pipeline assembly, real ground and underground pipelines are simulated, multi-person drilling operation can be carried out, and the use is flexible; through the arrangement of the main well mouth, the main well pipe and the maintenance bin, the situation of entering the maintenance bin for drilling can be simulated, and through the arrangement of the side well pipe, when drilling rescue work is simulated, ventilation from the side well pipe and rescue from the main well pipe can be simulated.

An application programming interface, API, and its implementing functions provide software code that can be incorporated into a simulated reality application and that determine a total calibration gain that is to be applied during run time of the application, to the audio signal of a particular digital audio asset that has been selected by the author of the simulated reality application. The total calibration gain includes at least a loudness correction gain that is determined based on a user-specified sound level parameter indicated through the API by the author. Other aspects are also described and claimed.

Computer-readable medium containing instructions that configure a computer to: present an application programming interface (API), wherein the API includes a user-specified sound level parameter; receive, via the API, one or more values ​​for the user-specified sound level parameter, which are assigned to a digital audio asset;and incorporating code into a simulated reality application that is currently being assembled, wherein the code determines a loudness correction gain for the digital audio asset by determining a difference between i) the one or more values ​​for the user-specified sound level parameter and ii) a parameter of the playback hardware device that represents a known or predefined sound level that can be produced by a playback hardware device on which the simulated reality application is running, wherein the loudness correction gain compensates for the difference, and the loudness correction gain is then to be applied to the digital audio asset during the runtime of the simulated reality application.

The present invention provides a modular, multifunctional karst collapse physical simulation experimental platform, including a rigid frame, a bearing device, a mobile device, a loading device, a lifting device, a pile foundation construction dynamic load simulation device, a ground vehicle dynamic load simulation device, a rainfall simulation device, a computer vision monitoring device, a groundwater pumping simulation device, and an underground space excavation disturbance simulation device. The mobile device is arranged on the bearing device, the lifting device, the loading device, and the pile foundation construction dynamic load simulation device are arranged on the mobile device, the vehicle dynamic load simulation device is connected to the traction device of the mobile vehicle, and the camera monitoring device and the rainfall simulation device are arranged on the rigid frame through a bracket. The present invention fully considers the key disaster-causing conditions in the urban environment, covers a wide range of working scenarios, and has strong applicability; the overall modular design is adopted, and each module can be flexibly loaded according to demand, which can more realistically simulate the real environment and reproduce the catastrophic evolution process of ground collapse.

The invention relates to the technical field of graphic simulation systems, in particular to a hydraulic fracturing process simulation and optimization system based on a digital twin technology. The system comprises a real-time input unit, a probabilistic simulation unit, a self-adaptive assimilation unit and a risk analysis and control unit. The system generates a prior crack probability cloud by acquiring real-time data and combining with the proxy model; the core of the method is that monitoring data assimilation is utilized to generate a posterior crack probability cloud, and a simulation-reality credibility index and a probabilistic risk boundary are solved according to the posterior crack probability cloud; the system generates an adaptive control signal according to the index and feeds back the adaptive control signal to the assimilation unit; according to the method, false accuracy of traditional deterministic simulation is overcome, and quantification and visual display of crack uncertainty are realized.

The invention relates to a social network subject simulation system and method based on a large language model, and belongs to the technical field of cognitive social simulation. In order to fill up evolvable psychological and action mechanisms existing in the cognitive social simulation field, the social network subject simulation system and method are provided, virtual subjects with dynamic memory, reflection and social behavior capabilities are constructed, and interaction and information spreading of multiple subjects in a virtual social environment are realized. Therefore, the public opinion forming and spreading process in a real social network is simulated.

The application provides a defect detection and positioning method based on regional anomaly generation and multi-level reverse distillation, and relates to the technical field of industrial defect detection. The new synthetic anomaly method provided by the application simulates the randomness of the abnormal area in the real scene by generating pseudo-anomaly images of different sizes and shapes, provides rich training data for the model, proposes a single-scale repair strategy including convolutional transformer processing and C-CBAM attention mechanism, enables the student network to efficiently capture global and local features, and realizes basic feature repair, further proposes a multi-scale repair strategy, removes redundant features by using a similarity redundancy removal module to enhance cross-layer feature integration, retains key information, and removes redundant features, simultaneously uses a multi-scale patch block fusion module to strengthen local fine-grained anomaly feature reconstruction, and finally realizes image anomaly detection and positioning through loss calculation and anomaly scoring. The method has good defect positioning effect and can meet the needs of industrial production.

In one implementation, a non-transitory computer-readable storage medium stores program instructions computer-executable on one or more processors of an electronic device to perform operations. The operations include presenting, on a display of the electronic device, a simulated reality (SR) environment at a first immersion level, where the first immersion level is associated with a first location of a reality boundary. Using a rotatable input device of the electronic device, input is received representing a request to change the first immersion level to a second immersion level. In accordance with receiving the input, the SR environment is presented at the second immersion level, where the second immersion level is associated with a second location of the reality boundary.

A method is provided for evaluation of data, where it was surprisingly found out that raw data can be simulated using hardware devices. The method actively operates and control hardware components to establish a network that provides hardware components that simulate the relationships between real world concepts. The method is able to automatically perform technical processes such that firstly no human ado is required and secondly the resulting data is not prone to errors. The method suggests iterations on evolving data sets and hence a bias is excluded or at least minimized in each iteration. Also provided is a respectively arranged system along with a computer program product and a computer-readable medium.

The invention belongs to the field of intelligent unmanned cluster control, and particularly relates to a bipartite cooperative control method of an intelligent unmanned cluster system, which is used for cooperative control in an unmanned aerial vehicle cluster system with two state updating modes. The communication weight is a positive value when the intra-group unmanned aerial vehicles communicate, the communication weight is a negative value when the inter-group unmanned aerial vehicles communicate, and an unmanned aerial vehicle adjacency matrix is established according to the communication weight; one group of unmanned aerial vehicles updates the state based on behavior dynamics, one group of unmanned aerial vehicles updates the state based on a protocol, and optimal state updating is obtained by solving Nash equilibrium according to an unmanned aerial vehicle state updating strategy and an adjacent matrix; and judging whether the intelligent unmanned cluster system converges or not and determining a steady-state position, and performing unmanned aerial vehicle control according to the obtained steady-state position. According to the method, the dependence of a traditional method on a system dynamics model is overcome, and real reality scenes with dynamics mixing performance such as unmanned driving and human driving in real life are simulated.

Methods and systems are provided for digitally replicating a real-world infrastructure to simulate the behavior of a real-world object, the methods and systems supporting the ability to extend a wireless network by providing services implemented in the network, and supporting optimization of network usage and digital representation accuracy. In one embodiment, the method includes instantiating one or more digital representation (D-Rep) instances corresponding to a digital replica of the real world object included in the real world infrastructure to form a digital infrastructure (D-Inf), and generating one or more digital representation (D-Rep) instances corresponding to a digital replica of the real world object included in the real world infrastructure. The method further includes providing a communication plane to provide a service to the D-Inf. The method further includes connecting to the real world object using the communication plane to collect real world data defining a state of the real world object, and associating the real world data with the D-Rep instance; the behavior of the real-world object is simulated by the D-Rep instance using a simulator that can be accessed by the D-Inf instance using the communication plane.

A first world is one of a real world and a virtual world simulating the real world, and a second world is another of them. A first image is captured by a first camera in the first world, and a second image is captured by a second camera in the second world. A visual positioning system executes common processing that generates a scene graph representing a positional relationship between objects included in the image and extracts a feature amount of the scene graph. The visual positioning system performs matching between a first feature amount extracted by the common processing on the first image and a second feature amount extracted by the common processing on the second image, and then associates the first camera position in the first world and the second camera position in the second world with each other based on a result of the matching.

The invention provides a defect detection and positioning method based on regional anomaly generation and multi-level reverse distillation, and relates to the technical field of industrial defect detection. According to the new anomaly synthesis method provided by the invention, the randomness of an abnormal region in a real scene is simulated by generating pseudo-anomaly images with different sizes and shapes, and rich training data is provided for a model; a single-scale repair strategy is proposed, the single-scale repair strategy comprises convolution transformer processing and a C-CBAM attention mechanism, so that the student network efficiently captures global and local features, and basic feature repair is realized; a multi-scale repair strategy is also provided, cross-layer feature integration is enhanced by means of a similarity redundancy removal module, key information is retained, redundant features are removed, and local fine-grained abnormal feature reconstruction is enhanced by means of a multi-scale patch block fusion module; and finally, through loss calculation and anomaly scoring, realizing anomaly detection and positioning of the image. The method has a good defect positioning effect and can meet the requirements of industrial production.

In some embodiments, an advanced packaging design and cost estimation system is provided. It may include a user interface incorporating a 3D canvas area where users can drag and drop packaging objects to model real world chiplets and packaging architecture scenarios and receive feedback on the predicted costs.

The embodiment of the invention discloses an action simulation method and a related device, on one hand, a target preparation action can be executed before the target action is executed, so that the authenticity of a game is improved by simulating the preparation action required for executing the target action in a real scene; the situation that the action authenticity is reduced due to direct execution of the action indicated by the instruction is avoided; and on the other hand, in the process of executing the target preparation action, the lens position can change along with the change of the posture of the game object, so that the visual change caused by the posture change is simulated through the change of the game scene area displayed by the game interface, the sense of reality of the target preparation action is further improved from the visual dimension, and the user experience is improved. And more real game experience is brought to players.

The invention discloses an artificial intelligence generated image detection model optimization method, system and device and a medium, which are corresponding schemes, and in the scheme, a dynamic interaction optimization mechanism is constructed between a finite available generation model and a to-be-optimized detection model; the performance of the detection model is continuously optimized by simulating a generative model-detection model alternate evolution path in the real world, so that the stable detection performance of the detection model in a real scene is ensured; the method can be applied to various current mainstream detection model architectures, and is wide in application range; meanwhile, images generated by various latest generation models can be detected, generalization is high, practicability is high, and the average identification precision in an experiment can reach 85% or above.

The application discloses a karst collapse column water inrush disaster simulation device and method, including a support box body and a control mechanism, the support box body is provided with an experimental main body mechanism, the support box body is provided with a water circulation unit; the experimental main body mechanism includes the simulation box of the top open, the front side wall of the simulation box is provided with an observation window, the inside of the simulation box is divided into water-bearing layer chamber, aquiclude chamber and sandstone layer chamber from bottom to top by the first baffle and the second baffle with through holes, the simulation box is also provided with the first collapse column cavity and the second collapse column cavity which are connected in parallel, the second collapse column cavity is connected with the damage zone cavity, the top of the damage zone cavity is provided with a coal seam simulation unit, the whole device can control the coal seam simulation unit and the water circulation unit through the control mechanism, can directly and visually simulate the whole process of water inrush disaster related to collapse column in the real coal seam mining process, improves the prediction accuracy of water inrush disaster data, and predicts and warns the disaster.

The invention relates to a world language user number dynamic prediction method based on multi-dimensional features. The method comprises the steps of S1, collecting multiple target languages and multi-dimensional factor data of sample regions corresponding to the target languages; s2, based on the multiple target languages and the multi-dimensional factor data of the sample regions corresponding to the target languages, the influence degree between the number of users using the target languages as the first language and the natural growth rate of the population and the influence degree between the number of users using the target languages as the second language and factors except the natural growth rate of the population in the multi-dimensional indexes are quantified; and S3, constructing a multi-dimensional language prediction model, and predicting the future trend of the number of language users through the multi-dimensional language prediction model. By adopting the method, the complex language use environment in the real world can be simulated more truly, and the comprehensiveness and accuracy of prediction are remarkably improved.

The utility model relates to the field of devices for demonstration in the industrial production process, in particular to a virtual simulation welding simulation system. The virtual simulation welding simulation system comprises a virtual simulation welding host, a welding gun model, a welding rod model and a welded piece model, the welding rod model and the welded piece model are clamped on the welding gun model, and the welded piece model comprises a welded piece model body and a simulation welding seam arranged on the welded piece model body. And an electromagnet is arranged at the simulated weld joint of the welded piece model body or the end part of the welding rod. The effect that the electromagnet enables the welding rod model and the welded piece model to be attracted under the electrified condition is used for simulating the situation that a welding rod adheres to a welded piece in reality, and the problem that an existing system cannot simulate the situation that the welding rod model adheres to the welded piece model is solved.

The invention provides a project recommendation model training method and device, a project recommendation method and device and electronic equipment, and belongs to the technical field of artificial intelligence, and the method comprises the steps: constructing a directional missing sample set, a random missing sample set and a non-missing sample set based on a training sample set comprising a plurality of training samples; the training sample comprises a user multi-modal operation feature vector sample and a corresponding item recommendation result label; and performing bidirectional optimization training on the project recommendation model and the corresponding deviation model by utilizing the directional missing sample set, the random missing sample set and the non-missing sample set to obtain the project recommendation model. According to the invention, the directional missing sample set, the random missing sample set and the non-missing sample set are constructed based on the training sample set to simulate the data deviation in reality, and the three sample sets are utilized to carry out bidirectional optimization training on the project recommendation model and the corresponding deviation model at the same time. Through fusion of multi-modal data and a deviation elimination mechanism, the deviation of a project recommendation model is significantly reduced.

The invention discloses a testing method and testing equipment for a positioning device and a computer readable storage medium. The method comprises the steps of obtaining to-be-simulated environment parameters, and generating a test scene based on the to-be-simulated environment parameters; the test scene comprises at least one of urban canyons, tunnels, indoor and outdoor transition, high-speed movement, ground-satellite network switching and complex electromagnetic interference; the to-be-simulated environment parameters comprise test scene environment parameters, motion parameters, trigger parameters and evaluation parameters; generating a dynamic track of a target object corresponding to the test scene, wherein the target object is correspondingly coupled with a positioning device; controlling the target object to run along the dynamic track, and collecting position information of the target object through a positioning device; and evaluating the performance of the positioning device by using the position information collected by the positioning device and the error information of the actual position information of the target object in the test scene. The positioning module is automatically tested by simulating a complex environment in reality, and the testing efficiency is improved.

A computer implemented method of creating a simulated realistic virtual model of a geographical area for training an autonomous driving system, comprising obtaining geographic map data of a geographical area, obtaining visual imagery data of the geographical area, classifying static objects identified in the visual imagery data to corresponding labels to designate labeled objects, superimposing the labeled objects over the geographic map data, generating a virtual 3D realistic model emulating the geographical area by synthesizing a corresponding visual texture for each of the labeled objects and injecting synthetic 3D imaging feed of the realistic model to imaging sensor(s) input(s) of the autonomous driving system controlling movement of an emulated vehicle in the realistic model where the synthetic 3D imaging feed is generated to depict the realistic model from a point of view of emulated imaging sensor(s) mounted on the emulated vehicle.

The present invention relates to a multi-scale cross-modal data enhancement method and system under risk disturbance, thereby providing a more comprehensive and accurate data foundation for digital intelligence-driven urban agglomeration applications; multi-domain cross-modal perception data of urban agglomerations at multiple spatiotemporal scales have problems such as local missing, sparse sampling, noise disturbance, and unclear patterns. By exploring data enhancement methods under risk disturbance, the originally discrete human mobility behavior data can be serialized and the missing values ​​in the samples can be filled to ensure the continuity of the samples in time, space and multiple scales, thereby improving the overall quantity and quality of the samples. With the help of data enhancement technology, various noises and disturbances can be introduced to simulate the real situation of the real world, thereby improving the robustness and generalization of the model. The process of samples from sparse to continuous, quality from missing to complete, model from local to global, and patterns from fuzzy to clear is realized, so as to better understand the inherent properties and associations of the data.