Digital human-oriented ultralimit multi-mode microenvironment simulation system and interaction method

Abstract

The invention discloses a digital human-oriented ultralimit multi-mode microenvironment simulation system, which dynamically generates ultralimit geological and climatic environments such as volcano, hurricane and extremely cold and extreme environments such as air / gravity / atmospheric pressure / sunlight irradiation / radiation exceeding the earth normal state, and combines a digital human injury-adaptation model and multi-mode interaction logic. And the limit test and experience of the digital human in the virtual world are realized. The innovation of the method comprises: 1) an overrun environment parameter generation technology (supporting thousand times of environment intensity of reality); the system is suitable for the fields of virtual tourism, space research, old people behavior analysis and the like, and standardization and commercialization of the digital human technology are promoted.

Description

Technical Field

[0001] The present invention belongs to the technical field of metaverse digital humans, and specifically relates to an ultra-limit multi-modal microenvironment simulation system designed specifically for digital humans. Through dynamic environment generation, AI behavior modeling, and multi-modal feedback technologies, it constructs geological disasters and extreme climate environments that exceed the limits of the physical world for digital human behavior testing, emotion simulation, and virtual experience content generation. Background Art

[0002] The existing technologies have the following three limitations. First, environmental restrictions: Traditional metaverse environment simulation systems (such as patent CN119292466A) are limited by real physical rules and cannot simulate extreme conditions such as ultra-high temperature and ultra-high gravity. Second, the singularity of digital human interaction: Existing digital human behavior models (such as patent CN119516063A) only support basic emotional feedback and lack a dynamic adaptation mechanism to extreme environments. Third, the limitation of application scenarios: Existing virtual experience systems are mostly oriented towards human users and do not design independent testing and observation tools for digital humans (such as patent CN117742496A).

[0003] The present invention constructs a completely virtualized ultra-limit environment to unleash the behavior potential of digital humans under extreme conditions and fills the gap in dedicated testing and experience tools for digital humans in the metaverse. Summary of the Invention

[0004] The core modules of the present invention include an ultra-limit environment generation engine, a digital human AI behavior model, an interaction mode controller, and a content generation and output module (see Figure 1 ).

[0005] The parameter range of the ultra-limit environment generation engine (see Figure 2 ): It supports ultra-limit parameters such as temperature (-200°C to 3000°C), humidity (0 - 1000%), gravity (0 - 100G), wind speed (0 - 1000m / s), radiation intensity (0 - 100kW / m²), etc.; Disaster simulation library: It pre-sets 20 types of geological climate models such as volcanic eruptions, tsunami waves, polar blizzards, and thunderstorm electric fields, and supports custom combinations (such as "Martian sandstorm + minus 150°C").

[0006] The dynamic damage calculation in the digital human AI behavior model (see Figure 3 ): Based on a physical engine (such as NVIDIA PhysX) and physiological simulation algorithms, it calculates the impact of the environment on the digital human "body" in real time (such as high-temperature melting and high-pressure deformation); Emotion-behavior mapping: Through an LSTM model, it associates environmental stress with the digital human's emotional state (fear value, excitement value) to drive behavior decisions (evasion / adaptation / collapse).

[0007] The interaction mode controller provides three digital human mode selections: Real Human Mode: Simulates human physiological limits, and environmental damage can lead to "virtual death" (triggering system reset); Invincible Mode: Ignores environmental damage and is used to observe behavioral potential under extreme conditions; Damage Controllable Mode: Customizes the damage coefficient (e.g., only retains 30% pain feedback).

[0008] The content generation and output module includes multimodal recording and automatic material generation. Multimodal recording: Captures digital human actions, expressions, voice data, and environmental parameter changes; Automatic material generation: Converts the interaction process into short videos (including special effect subtitles), 3D scene models (Unity / Unreal format), or social media interaction scripts (such as Twitter hashtag + #DigitalSurvival).

[0009] The technical process is as follows: User configures environmental parameters → Loads the digital human AI model → Starts real-time simulation → Performs dynamic damage calculation → Provides emotion-behavior feedback → Conducts multimodal recording → Generates and outputs content (see Figure 4 )

[0010] The core innovation of this invention is reflected in three aspects: the dynamic generation technology of extreme environments, the digital human damage-adaptation model, and multi-mode switching and commercial output.

[0011] Dynamic generation technology of extreme environments: Breaks through the limitations of traditional metaverse environments, uses fractal noise algorithms to simulate disaster scene details (such as the chaotic form of volcanic lava flow); Introduces distributed resource management technology to support parallel computing of thousands of parameters (such as simultaneously simulating the coupling effect of a hurricane and an earthquake).

[0012] Digital human damage-adaptation model: Creates a "virtual tissue damage algorithm" to gradually destroy the digital human "body" structure according to the environmental intensity (such as epidermal carbonization → muscle melting → bone fracture under high temperature); Dynamic learning mechanism: The digital human autonomously evolves anti-pressure strategies through reinforcement learning (PPO algorithm) (such as learning to find an insulating shelter during a thunderstorm).

[0013] Multi-mode switching and commercial output: Provides an API interface for third parties to call environmental data and digital human behavior logs (such as game developers obtaining motion capture data of "the digital human survived in magma for 10 minutes"); Combines NFT technology to convert the digital human "survival achievements" into tradable assets (such as "polar survival certification badge").

[0014] Industrial Design Description: In terms of hardware compatibility, it supports cloud deployment (AWS / GCP) and local servers (NVIDIA DGX Station). The minimum configuration requirements are: RTX 4090 graphics card, 64GB of memory, and 1TB SSD. In terms of security and ethics, the "virtual death" of the digital human requires secondary confirmation by the user to avoid accidental data deletion. It follows the behavior norms of digital humans in the metaverse and prohibits simulating anti-human scenarios.

[0015] The comparison between the present invention and the traditional metaverse environment system is shown in Table 1: Table 1: Technical Comparison and Advantages Comparison item Traditional metaverse environment system The present invention Environmental limit Limited by real physical rules Support thousands of times of parameters such as ultra-high temperature and ultra-high gravity Digital human interaction Only basic action feedback Dynamic damage calculation + emotion-behavior mapping Commercial output No dedicated content generation tool Automated short videos, 3D models, social scripts Description of the Drawings

[0016] Figure 1 : System architecture diagram (environment generation → AI model → content output).

[0017] Figure 2 : Schematic diagram of the over-limit environmental parameter range (volcano / hurricane / extreme cold).

[0018] Figure 3 : Digital human injury level model (epidermis → bone injury).

[0019] Figure 4 : Interactive mode switching logic flowchart (real person / invincible / controllable mode). Detailed Implementation Manner

[0020] Example 1: Virtual extreme tourism experience. Scenario configuration: Simulate the eruption of Kilauea Volcano in Hawaii (temperature 1200°C, 10 times the lethal dose of SO 2 concentration); Digital human mode: Injury controllable mode (pain feedback 50%); Output content: Generate a 15-second short video showing the digital human running in the lava flow and triggering the "skin carbonization" special effect, with the topic #VolcanoChallenge attached.

[0021] Example 2: Space psychology research. Scenario configuration: Sandstorm in a Mars base (wind speed 200m / s, air pressure 0.01kPa, radiation intensity 5kW / m²); Digital human mode: Real person mode (simulating the psychological breakdown threshold of astronauts); Scientific research application: Record the emotional fluctuation data of the digital human during 72 consecutive hours of isolation to optimize the psychological intervention plan for the manned Mars mission.

[0022] Example 3: Observation of the behavior of the elderly. Scenario configuration: Walking on ice (friction coefficient 0.05, temperature -30°C); Digital human mode: Invincible mode (disabling fall injuries); Application in nursing homes: Simulate the stability of the elderly with different gaits on ice through digital humans to design an optimized plan for anti-slip shoe equipment.

Claims

1. A super-limited multi-modal micro-environment simulation system for digital humans, characterized by It includes an ultra-limited environment generation engine, a digital human AI behavior model and a content output module, wherein: the environment generation engine supports ultra-limited geological and climatic environments such as volcanoes, hurricanes, and extreme cold, as well as parameter simulations when air / gravity / atmospheric pressure / sunlight exposure / radiation exceed the normal state of the earth, and allows customized environment combinations; the AI ​​behavior model drives the adaptive behavior of digital humans in extreme environments through dynamic damage calculation and emotion mapping; the content output module converts the interaction process into social media materials and scientific research data sets.

2. The system according to claim 1, characterized in that The ultra-limited environment generation engine adopts a fractal noise algorithm to simulate the details of disaster scenes and supports parallel calculation of thousands of parameters.

3. The system according to claim 1, characterized in that The digital human AI behavior model includes a virtual tissue damage algorithm and a reinforcement learning mechanism to achieve layer-by-layer destruction simulation from the epidermis to the bones.

4. The system according to claim 1, characterized in that The interactive mode controller provides a real-life mode, an invincible mode, and a damage controllable mode, and supports customization of a pain feedback coefficient.

5. The system according to claim 1, characterized in that Through NFT technology, the "survival achievements" of digital people are converted into tradable assets, and an API interface is opened for third parties to call behavioral data.

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