118 results about "Physics engine" patented technology

A physical AI-based magnetic field environment modeling method and a physical AI-based magnetic field environment modeling system are disclosed, the physical AI-based magnetic field environment modeling system comprises a data layer, a preprocessing layer, a core modeling layer and a verification and application layer, and the core modeling layer comprises a physical knowledge base and stores physical laws, material constitutive relationships and boundary conditions related to a target magnetic field environment; the model construction module is responsible for designing and constructing a main body structure of a physical AI model according to problem characteristics and a physical knowledge base; the physical AI engine represents a constructed or trained physical AI model instance, receives input and quickly outputs a predicted magnetic field value; and the model training module is responsible for training the neural network model generated by the model building module by using the preprocessed data and physical constraints in the physical knowledge base. The core innovation point of the invention lies in that a physical artificial intelligence normal form is systematically introduced and applied to the modeling process of a complex magnetic field environment, and an efficient, accurate, robust and physically consistent magnetic field modeling system is created through deep fusion of physical laws and data driven learning.

The invention belongs to the field of software testing and defect detection, focuses on reliability verification of a physical simulation engine, is suitable for scenes depending on physical simulation, such as robot simulation, automatic driving testing, unmanned aerial vehicle control, education and scientific research, and particularly relates to a variation-based physical simulation engine defect detection method. Potential defects of core modules of collision detection, mechanical calculation, dynamics and the like are efficiently found through a variation test method. According to the method, a feature library is constructed through static library API analysis and AST / IR code analysis, test code expansion is performed by utilizing a large model, a test driver adaptive to a specific data type is generated, a physical semantic constraint mutation seed is combined, a test is executed through libFuzzer, defect and coverage rate data are analyzed, a use case selection strategy is optimized, and the test efficiency is improved. Defects of core modules such as collision detection and dynamic solution are efficiently detected, and the test pertinence and efficiency are improved.

The invention discloses a mechanical arm simulation system supporting industrial quality inspection, which relates to the technical field of industrial automation and comprises a multi-physics field simulation engine module, a digital twin interface module, a defect sample library module and a cooperative control module. According to the method, traditional entity mechanical arm debugging is replaced by rigid body dynamics simulation based on a physical engine, loss and production line shutdown caused by repeated trial and error of equipment are avoided, rapid construction of the digital twin environment of the production line is achieved by means of an efficient CAD model conversion process and a lightweight loading technology, and high-fidelity optical simulation is achieved through a parameterized defect model library and high-fidelity optical simulation. Various common industrial defects and complex optical effects are covered, the modeling bottleneck of a quality inspection scene is broken through, real-time closed-loop interaction of visual inspection and motion control is realized by using thread separation and an efficient communication technology, and the recognition robustness of a visual algorithm to tiny defects is guaranteed; the reliability of algorithm verification is improved through the quantitative output of algorithm performance indexes and the comprehensive test of extreme working conditions by the simulation system.

The invention relates to the technical field of robot control, in particular to a cross-modal perceptual driving body robot compliance control system which comprises the steps that a sensor is adopted to synchronously collect environment information, multi-source data bias is eliminated through a space-time alignment algorithm, a radial basis function neural network is adopted to analyze multi-modal fusion features, and a multi-modal model is obtained; human operation intention probability distribution is extracted to decompose a task into a path planning layer and a motion control layer, a collision-free trajectory is generated through an RRT algorithm, a high-fidelity physical engine is adopted to construct a virtual interaction scene, and robot learning results are shared through federal learning. According to the method, the problems of inaccurate perception, incoordination between intention recognition and interaction control, difficulty in control strategy verification, slow new task adaptation and difficulty in multi-robot learning result sharing caused by multi-source data deviation and large multi-modal semantic difference of the body robot in a complex environment are solved.

The invention discloses a coal mine robot cluster-oriented virtual entity synchronous mapping method. The method comprises the following steps of: constructing a virtual entity synchronous mapping system consisting of a coal mine robot cluster physical entity, a coal mine robot cluster virtual entity, coal mine robot cluster twin data, cluster service application and information interaction; a coal mine robot cluster is used as a physical entity object, an OPC UA communication protocol is used for data collection, the collected data is processed, a virtual entity is driven in a script mode based on a Unity 3D physical engine, and therefore a virtual-real mapping channel is established; converting various non-standardized data structures of the robot cluster into standardized data structures; data of the heterogeneous robot are collected and transmitted through standardization of various communication protocols, and the data are used for driving the virtual entity model. The method has the advantage of performing synchronous mapping on the virtual entities so as to facilitate intelligent management and control.

The invention discloses a neurosurgical operation virtual simulation training system based on multi-modal data fusion, and relates to the technical field of operation simulation. The data acquisition and preprocessing module acquires data such as images and force feedback, and standardized storage is performed after filtering and registration; the multi-modal data fusion module performs weighted fusion on the data by using an attention algorithm to generate a three-dimensional model; the virtual operation scene construction module generates a high-fidelity environment through ray tracing and a physical engine; the surgical operation interaction simulation module realizes accurate interaction through positioning tracking and force feedback; the training evaluation and feedback module quantifies operation performance and provides guidance; and the system management and iteration module guarantees operation and supports data updating and optimization. According to the method, a high-reality scene is constructed through multi-modal fusion, interaction and multi-dimensional evaluation help skill improvement, dynamic difficulty and personalized paths are adaptive to different users, collaborative training and privacy data collaboration are supported, operation training standardization is promoted, and the risk of errors in an operation is reduced.

The invention discloses a simulation test method and system for an unmanned aerial vehicle control algorithm, relates to the field of intelligent system simulation test, and can solve the defects of an unmanned aerial vehicle simulation system in high real scene rendering and physical engine precision at the present stage. The method solves the problems that the real characteristics of a visual sensor and a flight platform cannot be accurately simulated, the performance of an algorithm in a complex real scene is difficult to effectively evaluate, and the adaptability of the algorithm to a hardware environment is difficult to verify, and comprises the following steps: constructing a high-trueness virtual environment according to scene requirements and rigid body dynamics simulation requirements of an unmanned aerial vehicle simulation test; constructing a simulation model according to the physical motion characteristics of the unmanned aerial vehicle hardware and the performance of the sensing equipment; importing the simulation model into a high-reality virtual environment, and performing parameter setting on the simulation model; and testing and verifying a control algorithm of the unmanned aerial vehicle based on the high-trueness virtual environment and the simulation model completed by parameter setting. The method is used for performing simulation test and verification on the control algorithm of the unmanned aerial vehicle.

The invention discloses a real-time software deformation interaction method based on a physical engine in an environment. The real-time software deformation interaction method comprises the following steps: S1, establishing a virtual environment and a software model; s2, constructing an interactive perception and collision detection network; s3, receiving and analyzing a multi-modal interaction instruction; s4, real-time deformation calculation based on a physical engine; s5, performing multi-user collaborative state synchronization and rendering feedback; and S6, carrying out fault state simulation on the software object. According to the method, real-time and high-precision simulation of software deformation is realized through deep fusion of software dynamics calculation of a physical engine and an interaction instruction stream, and through hierarchical physical attribute binding and client prediction, the network synchronization data volume is greatly reduced while the millimeter-level deformation precision is ensured, so that the network synchronization efficiency is improved. And low-delay and high-consistency experience under multi-person cooperative operation is ensured.

The invention discloses a virtual hand grabbing method and system for mixed reality interaction, which is based on a hinge proxy hand model, utilizes a hand tracking device and a physical engine, and fuses hand key point tracking data and a force closing algorithm, and is a grabbing method which is based on physical simulation, is real-time and efficient and does not need to predefine object information. High-precision and real-time hand-object interaction is realized, a virtual hand observed by a user in a mixed reality picture is effectively prevented from penetrating through a virtual object, and the interaction experience in VR / AR equipment is remarkably improved. Moreover, the method supports the real-time adjustment of the dynamic grabbing gesture based on the surface of the object, and is suitable for various VR / AR devices.

The invention relates to the technical field of property management, and discloses an intelligent property management platform and management method combined with AI scene simulation, and the platform comprises a dynamic scene twinning engine which is used for constructing a community total-factor digital twinning body fusing the state of Internet of Things equipment, user behaviors and environment data in real time, and carrying out the dynamic simulation through a physical engine, the model comprises a scene slice and a self-feedback twinborn model; the multi-modal data fusion layer adopts an event-driven data pipeline and is used for correlation analysis of multi-source heterogeneous data; and the decision tree is used for carrying out self-evolution decision making based on a dynamic twin simulation result, and a decision confidence attenuation model is introduced into the decision tree. According to the invention, the bottleneck of passive response in traditional property management is changed, a dynamic scene twin engine is constructed in a foreseeing manner, the property management is converted from a passive operation and maintenance mode depending on manpower and regular inspection into a mode capable of predicting equipment faults in advance and actively providing services, and the intelligence and foreseeing level of the property management is improved.

The invention discloses a multi-robot intelligent collaborative simulation training system based on an augmented reality technology, and relates to the technical field of intelligent warehousing and logistics automation. An AR dynamic obstacle generation technology breaks through static limitation of a traditional simulation scene, sudden interference such as container collapse, temporary forbidding and the like is simulated through a physical engine, and real-time simulation is achieved. A training strategy is directly exposed to a high-simulation risk environment; a topology potential field decision-making mechanism is introduced to quantify course conflicts and distance threats into a repulsive force field in a unified mode, a course Gaussian modulation item accurately filters non-direct collision targets, and the oscillation defect of a traditional potential field method is avoided. According to the path entropy calculation, the conflict probability is analyzed through direction density distribution, gradient adjustment is forcibly activated when the entropy of a narrow channel exceeds a threshold value, the chain reaction of high-density deadlock is restrained from the source, and the group path fluency is guaranteed.

A system and method for adaptive ideation and innovation management using graph-based similarity computation and real-time social facilitation are disclosed, and the system may include a plurality of client devices operated by a human user and one or more AI Agents. The system may further include a computing platform running a Precompute Similarity Engine that may be configured to embed and index idea objects, precompute similarity clusters, and generate candidate merge or purge operations together with diversity and novelty signals; and running a Social Physics Engine that may be configured to monitor human user and machine participant (AI agent) interactions, compute group metrics, and issue digital facilitation interventions. The Precompute Similarity Engine and the Social Physics Engine may operate in an interdependent feedback loop such that diversity and novelty signals guide the generation of digital facilitation interventions that are communicated via the network to the plurality of client devices and the one or more AI Agents.

The invention discloses an unmanned tower crane dynamic simulation method and system based on a virtual simulation technology, and relates to the technical field of intelligent construction. Comprising the following steps: constructing an unmanned tower crane BIM model and collecting point cloud data, and establishing a simulation model based on the unmanned tower crane BIM model and the point cloud data; developing a customized physical engine based on the simulation model, and constructing a multi-body dynamic model; constructing a three-dimensional wind field model, adjusting parameters, performing climate coupling simulation with the multi-body dynamic model, and obtaining structure response data under different wind fields; constructing an unmanned tower crane path planning model, and generating and executing an unmanned tower crane motion path in combination with the wind field parameters and the structure response data; running state data are obtained and visualized, and multi-dimensional risk monitoring is carried out on the path execution process according to the running state data. According to the method, the problems of scene distortion, rough simulation and risk missed judgment in the existing unmanned tower crane virtual rehearsal are solved, and the authenticity and effectiveness of the virtual rehearsal are improved.

The invention discloses a cavity robot real-time control method based on a dynamic safety boundary and a related device. The method comprises the following steps: establishing a dynamic security rule base, and activating corresponding constraints in real time according to organization characteristics obtained by sensor fusion; the fusion state information is converted into a symbol track in a discrete time step, and a timed automaton is used for online detection whether the current security constraint is met or not; if not, sampling under a model prediction control framework to generate a control sequence, predicting a track through a physical engine, then verifying point by point by using a safety rule, retaining a passing track, and selecting the track with the highest score as a new motion path; and analyzing the path into a speed instruction, and driving the robot to execute after passing through an impedance control loop and Lie group projection. According to the method, through safety rule dynamic updating and closed-loop verification, the collision risk in the operation is remarkably reduced, and the operation safety and real-time performance of the cavity robot are improved.

This invention discloses an immersive VR / AR-based method for training and remote collaborative operation and maintenance of a heating furnace. This invention achieves two-way AR / VR collaborative operation and maintenance functionality, enabling remote experts to provide real-time guidance to on-site personnel through 3D annotations, filling the technological gap between training and operation and maintenance. Simultaneously, this invention utilizes customized high-fidelity rendering tailored to the unique physical phenomena of the heating furnace, surpassing existing general-purpose physics engines. The AR application scenario of this invention involves collaboration between experts and on-site personnel, rather than individual learning by trainees. It employs SLAM + 3D point cloud to achieve precise alignment between virtual and real spaces, and uses a two-way communication protocol to achieve real-time mapping of interactive commands, solving the technical challenge of existing AR systems' inability to support remote expert collaboration.

The application relates to the field of virtual reality, and particularly discloses a display method and device for an environment object, which comprises the following steps: in response to a creation operation of an environment object contained in a virtual world application, acquiring an object generation time of the environment object; determining an associated object having an association relationship with the environment object, and acquiring an associated interaction time at which the associated object and the environment object interact; determining a time parameter of the environment object according to the object generation time and the associated interaction time; and displaying the environment object according to the time parameter. The method can accurately restore the real state of a real world, and compared with a traditional method of performing complex calculation through a physical engine, the method can reduce system resource consumption and improve display speed.

A distributed high-fidelity simulation system for large-scale high-speed AUVs based on real disturbance data is proposed. Through a large-scale AUV virtual test vehicle subsystem, the system simulates the motion state of a real large-scale high-speed AUV physical prototype under the interaction of rigid body inertia, gravity, buoyancy, inertial hydrodynamic forces, centripetal force, Coriolis force, drag, thrust, rudder force, and external environmental disturbances. Collision attributes are added to the prototype through a physics engine. The system also utilizes an underwater 3D virtual environment subsystem to render a large-scale underwater environment, build dynamic and static obstacle visualization models, and simulate the generation of realistic ocean currents and wave disturbances with high fidelity. The simulation presents a realistic underwater environment for a large, high-speed AUV. A motion solution subsystem describes the transformation relationships between the fixed coordinate systems of all objects in the underwater virtual environment and solves the motion equations of the large AUV, synchronously updating its pose and velocity states. A data management subsystem manages various data generated during the simulation, supporting write and read data operations, and also manages and coordinates data communication between nodes, supporting receive and send data operations. A visualization subsystem loads and dynamically displays the underwater 3D environment and the large AUV virtual test vehicle model, synchronously updating real-time data curves and visualizing the AUV's motion trajectory.

This invention discloses a method and system for generating self-evolving world models based on the synergy of rule-based and neural network dual engines, belonging to the field of artificial intelligence technology. The invention's overall concept is based on the collaborative autonomous evolution of dual-engine intelligent agents. Rule-based intelligent agents ensure decision-making stability, while neural network intelligent agents enable adaptive evolution in complex environments. The global state of the model is synchronously input into both engines. After the intelligent agent orchestrator fuses the decisions, the autonomous evolution engine automatically adjusts the model parameters and training strategies, achieving closed-loop autonomous evolution without human intervention. The system synchronously integrates a multimodal unified encoder, a differentiable physics engine, and a 3D Gaussian decoder. Each module is tightly coupled under a unified data flow, fully complying with the patent single-use requirement. This invention achieves integrated protection of the core architecture and auxiliary functions through a single patent, providing broad protection scope and strong decomposability. It is applicable to the fields of artificial intelligence world models, digital twins, AGI autonomous evolution, and 3D virtual scene generation.

The invention relates to the technical field of VR teaching, solves the technical problems of periodic grid distortion and visual jittering caused by illegal operation of students in a VR training system, and particularly relates to a VR display anti-jittering method applied to learning education. Collecting physical state parameters of the virtual device, constructing the physical state parameters into a basic data set, and converting the basic data set into a transition state set; and constructing a state space containing a plurality of physical state templates, and calculating a matching score of the transition state set and each physical state template. According to the method, the illegal operation is dynamically monitored, and a smooth interpolation transition technology is adopted, so that periodic picture jitter caused by physical engine conflict backtracking due to the illegal operation of a student is effectively avoided. Through a state buffer mechanism, natural transition of physical states (such as wear degree, glossiness, position and load) of equipment during rollback is ensured, and material flickering and visual mutation are avoided, so that immersion and operation accuracy of students are improved.

The invention discloses a humanoid robot motion control method based on reinforcement learning and Sim2Real migration, and particularly relates to the field of pedestrian robot motion control, and the method comprises the following steps: S01, constructing a robot model based on a physical engine, including terrain friction, inertia, noise and collision characteristics, and setting a joint angle and a speed upper limit; s02, learning a motion strategy in a simulation environment by adopting a PPO algorithm; s03, designing a reward function of a stable and efficient gait for guiding strategy learning; s04, parameter disturbance is introduced in training so as to reduce the real gap; and S05, deploying the simulation strategy to the real robot, and integrating a security mechanism. The humanoid robot motion control method aims at solving the problems that in the prior art, strong modeling is relied on, disturbance is sensitive, and deployment cost is high, the lightweight and self-adaptive humanoid robot motion control method is provided, rapid adaptation to uncertain environments (such as irregular terrains and external thrust) is achieved, and the falling risk in actual deployment is reduced.

The invention discloses an unmanned flight platform flexible obstacle active crossing method and a related device, and relates to the technical field of unmanned aerial vehicles, and the method comprises the steps: building a flexible obstacle interactive simulation environment based on a physical engine; in a flexible obstacle interactive simulation environment, taking a visual data flow and a state data flow of the unmanned flight platform as input, taking a motor accelerator instruction as output, and training a cascade deep neural network model based on a near-end strategy optimization algorithm; driving a sensor interface through an ROS system to obtain real-time vision and state data, inputting the real-time vision and state data to the trained cascade deep neural network model, and generating a motor control instruction; and determining an active crossing strategy of the unmanned flight platform according to the motor control instruction. The problems of extra load and pneumatic interference caused by a traditional protection device can be avoided.

The invention discloses an animation game 3D digital human personalized generation and interaction system, which relates to three-dimensional game modeling and comprises a user data acquisition module, a parameter decoupling generation engine, a real-time animation driving module and a multi-mode interaction feedback module. According to the personalized generation and interaction system provided by the invention, the personalized degree and the interaction experience of a digital human of a cartoon game are remarkably improved through a highly integrated technical module, user characteristics are accurately captured by utilizing a user data acquisition module, independent control and self-adaptive recombination of bones, skin and actions are realized in combination with a parameter decoupling generation engine, and the interaction experience of the digital human of the cartoon game is improved. High customization of the digital human is ensured, the real-time animation driving module enables the actions of the digital human to be more natural and smoother and micro expression control to be accurate and fine through fusion of a physical engine and voice emotion recognition, and the multi-modal interaction feedback module achieves cross-platform seamless interaction and enhances immersion by analyzing user gestures and environment data.

This invention discloses a system and method for psychotherapy that integrates virtual reality scenes, belonging to the interdisciplinary field of psychotherapy and virtual reality. It addresses the problems of fixed scenes, delayed adjustment, weak interactivity, and lack of cultural adaptability in traditional psychotherapy. The method includes using non-contact biosensors to capture facial blood oxygen fluctuations, combining this with a hemodynamic model to remove artifacts, and then quantifying these fluctuations into emotional energy values ​​based on an individual emotional sample set and an incremental learning algorithm to generate scene seeds containing parameters such as color temperature. A virtual physics engine is then driven to reconstruct elements such as light and shadow, and fluids, forming a physically-level dynamic scene. Inertial sensors capture user movements and convert them into virtual pressure gradients, constructing a coupled feedback loop between movement and scene. Psychological trends are predicted through hierarchical Fourier analysis of the seed sequence. This invention achieves real-time adaptation and proactive intervention between psychological states and virtual scenes, enhancing user immersion and cultural and emotional resonance, and improving the accuracy and effectiveness of psychotherapy.

The invention provides a man-machine cooperation conflict test case generation method and system, and the method comprises the following steps: S1, collecting a vehicle motion state, a driving operation behavior and a driver physiological state, carrying out the multi-modal data fusion modeling, constructing a personalized driving style model, and calculating driving style parameters; s2, detecting man-machine cooperation conflict behaviors in real time, and quantifying man-machine cooperation conflict levels; s3, inputting the man-machine collaboration conflict level and the driving style parameter as conditional variables into a generative adversarial imitation learning model to generate a man-machine collaboration conflict test case; s4, verifying the dynamics rationality of the man-machine cooperation conflict test case through a physical engine; and S5, distributing and iterating the man-machine collaborative conflict test case generation model by adopting a federated learning mechanism. The man-machine cooperation conflict test case generated by the method can truly simulate man-machine right and liability games and behavior contradictions existing in the actual driving process.

The invention discloses a ship lockage simulation method of self-adaptive time step length in a digital twinning scene, and belongs to the technical field of digital twinning and simulation. The method comprises the following steps: collecting and preprocessing ship motion state, ship lock structure and navigation rule data; a system architecture comprising a simulation layer, a control layer and a rule layer is constructed, the simulation layer adopts a multi-level physical engine cooperative computing mechanism, high-precision three-dimensional geometric modeling and real-time dynamic simulation are combined, and a self-adaptive time step control algorithm is introduced to dynamically adjust a simulation step in a key area so as to improve the precision; the control layer supports multi-ship-type dynamic parameter configuration through a modular ship behavior control model library; the rule layer drives navigation logic control through a rule engine, and flexibly executes rules such as single-line and double-line lockage and priority scheduling. According to the method, the problem of mold penetration caused by inaccurate collision detection in the prior art is effectively solved, and the universality, the flexibility and the intelligent level of multi-ship-type and multi-rule scenes are improved.

The simulation method comprises the following steps: acquiring at least one image and / or one video of a simulation environment; and in a first time period when the automatic driving simulation task is executed, simulation data of at least one virtual sensor of the vehicle in the first time period are obtained through simulation according to the at least one image and / or the video and the track information of the vehicle. According to the method, in the process of generating the simulation data of various virtual sensors, an environment model around the vehicle does not need to be constructed, the motion trails of other vehicles around the vehicle do not need to be independently predicted, and intermediate results such as road network information do not need to be generated, so that the structural complexity of a simulation module can be reduced. Moreover, according to the method, simulation data of various virtual sensors can be directly simulated according to the trajectory information of the vehicle and at least one input image and / or one input video, the authenticity of the simulation data can be improved, a physical engine and a graphic engine do not need to be used, and the structural complexity of a simulation module is further reduced.

The invention discloses a mixed domain adaptive bridge underwater disease detection method and system, and relates to the technical field of structure underwater detection. The method comprises the following steps: constructing a high-fidelity virtual simulation environment for underwater bridge detection based on a physical engine, and simulating underwater complex optical effects and disease geometric features by using a physical rendering technology; setting a camera guide rail to move along a preset path in a simulation environment, and automatically generating a synthetic data set with pixel-level labels; constructing a mixed domain training set containing real data and synthetic data; constructing a hybrid domain adaptive detection network; and training a mixed domain adaptive detection network by using the mixed data set and carrying out disease detection in a real scene. According to the method, the problem of scarcity of underwater detection data is solved by effectively utilizing a physical engine, and the detection precision and robustness are remarkably improved through mixed domain self-adaption.

The invention discloses a multi-rotor unmanned aerial vehicle fault-tolerant flight control method based on end-to-end direct thrust control, and the method comprises the steps: constructing a four-rotor unmanned aerial vehicle pure analysis micro simulation environment facing implicit feature observation and gradient back propagation, and embedding a continuous micro fault injection and execution mechanism mapping mechanism; a fourth-order Runge-Kutta method is adopted to carry out discretization iteration on the continuous operator; constructing an end-to-end control network based on spatial-temporal feature structured decoupling and hidden variable direct drive, and extracting and outputting a four-motor action instruction through double-current features; training an end-to-end control network in a micro-simulation environment, and optimizing control network parameters based on a micro-physical engine and time-based back propagation; and a self-adaptive composite loss function and a multi-order course learning mechanism are combined, so that the control network converges to an effective fault-tolerant control strategy. According to the method, self-adaptive control without an independent fault detection and diagnosis module under the single-motor fault can be realized, and a smooth transition mechanism from normal to single-motor failure is established.

The invention provides a full-scene interactive middle school physics virtual experiment teaching system. The system comprises a core experiment simulation module, the module utilizes a physical engine, a three-dimensional modeling technology, a virtual reality technology and an image and sound processing technology, a physical experiment process can be reproduced truly, a correct result can be provided for correct operation of students, and phenomena conforming to a real experiment can be presented for wrong operation; and a matched experimental data processing module supports acquisition, analysis and result presentation of experimental data. The system also integrates comprehensive teaching management functions of user management, course management, experiment management, teaching condition statistics, authority management and the like. On the basis, students can carry out high-quality experiments in a safe and convenient virtual environment, and understanding of physical theories is deepened through operation by themselves; meanwhile, the dependence of schools on entity laboratories and equipment is effectively reduced, the utilization efficiency of teaching resources and the flexibility of teaching are improved, and a powerful auxiliary tool is provided for physics teaching.