Virtual Mammal Eye Movement Simulation with Stabilization Constraints
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Solution Overview
Problem
Current simulation systems for the vision system of mammals, particularly in dynamic environments, fail to accurately replicate the complex interactions between eye movements and environmental changes, leading to unrealistic or distorted representations of physiological behavior.
Innovation Solution
A device and process that simulate a mammal's behavior in a virtual environment by using a head and eyes that can move independently, with a processor that assesses and adjusts movements based on stabilization constraints, allowing for learning and dynamic adjustment of eye movements through neural networks, enabling realistic simulation of voluntary and reflexive eye movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing simulation systems are used to model vision systems, then the simulation can be performed, but the simulation fails to accurately replicate complex interactions between eye movements and environmental changes
Solution Approach 1:
The vision system simulation is divided into separate functional modules: head movement module, eye movement module (including VOR and voluntary movements), environmental assessment module, and integration module. Each module handles specific aspects of the simulation independently, improving overall accuracy while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The simulation system incorporates feedback mechanisms where the processor continuously monitors eye positions, head movements, and environmental data to dynamically adjust the simulation parameters. This feedback loop ensures accurate replication of physiological behaviors such as VOR adaptation and voluntary eye movements in response to changing environmental conditions.
2Ease of operation
If static vision assessment conditions are used, then the assessment is simplified, but the assessment does not reflect practical varying visual environments
Solution Approach 1:
The system transitions from static to dynamic vision assessment by enabling the virtual mammal to move its head and eyes in response to varying environmental conditions. The simulation incorporates dynamic elements such as changing light conditions, moving objects, and adaptive eye movements, providing reliable assessment of visual performance under practical conditions while maintaining ease of operation through automated control.
3Measurement precision
If vestibulo-ocular reflex is implemented in the simulation, then the physiological accuracy is improved, but the computational complexity increases
Solution Approach 1:
The complex physiological VOR mechanism is replaced with a computational model that uses mathematical algorithms to simulate the reflex behavior. Instead of implementing the full biological system, the patent uses processed data from sensors and pre-programmed response patterns to achieve VOR-like behavior, reducing computational complexity while maintaining physiological accuracy.
Solution Approach 2:
The simulation system pre-calculates and stores VOR response patterns and eye movement trajectories in databases before the actual simulation runs. During execution, the processor retrieves pre-computed data rather than calculating everything in real-time, significantly reducing computational complexity while maintaining high physiological accuracy in the simulated eye movements.
Data Source
AI summary
A device for simulating a behavior of a mammal in an environment by a virtual mammal includes a mobile head and at least one mobile eye including a first input for successive data representative of eye poses, a second input for mobility action instructions, a memory for storing information on the environment and on stabilization constraints, at least one processor assessing a current part of the environment and recording information on said current part, triggering successive movements of the head and of the eye(s) in function of said mobility action, controlling a dynamic adjustment of the successive movements of the eye(s) with respect to the successive movements of the head in function of the successive data and by using the stabilization constraints. The device further comprises a third input for training data representative of a training movement sequence of the head and the eye(s) associated with a training environment.