Movable Object Simulation for Sensor Failure and Environment Testing
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Solution Overview
Problem
There is a need for a system that can simulate the operations of movable objects, such as UAVs, to test mechanical failures, sensor malfunctions, and interactions with the environment without requiring real objects or environments.
Innovation Solution
A movable object simulation system that uses models to simulate states, sensor data, and environment data, with a state simulator, vision simulator, and controller to generate control signals and visualize operations, allowing for the simulation of various scenarios without physical testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real movable objects and environments are used for testing, then testing accuracy and realism are improved, but cost, time, and safety risks increase
Solution Approach 1:
The patent creates virtual copies of movable objects, sensors, and environments through computer simulation models. These digital replicas allow testing of mechanical failures and sensor malfunctions without using physical objects, thereby reducing time and cost while maintaining testing accuracy through realistic simulation of failure modes and environmental conditions.
Solution Approach 2:
The simulation system acts as an intermediary between the designer and the physical world. It provides a virtual testing environment that mediates the evaluation of movable object performance, allowing comprehensive testing of failure scenarios without direct interaction with physical systems, thus reducing time and safety risks while preserving measurement accuracy.
2Measurement precision
If real movable objects and environments are used for testing, then testing accuracy and realism are improved, but cost, time, and safety risks increase
Solution Approach 1:
The patent creates virtual copies of movable objects, sensors, and environments through computer simulation models. These digital replicas allow testing of mechanical failures and sensor malfunctions without using physical objects, thereby reducing time and cost while maintaining testing accuracy through realistic simulation of failure modes and environmental conditions.
Solution Approach 2:
The virtual simulation environment provides a cost-effective alternative to expensive physical testing setups. The digital models can be created, modified, and discarded without material cost, allowing extensive testing of various failure scenarios and environmental conditions at minimal expense compared to physical prototypes and test equipment.
3Reliability
If comprehensive testing of mechanical failures and sensor malfunctions is performed, then reliability is improved, but device complexity and testing time increase
Solution Approach 1:
The simulation system is divided into separate functional modules: movable object models representing the physical system, sensor models simulating sensor behavior including failures, and environment models creating test scenarios. This segmentation allows each component to be developed and validated independently, reducing overall system complexity while enabling comprehensive reliability testing through coordinated interaction of modules.
Solution Approach 2:
The simulation framework provides universal functionality for testing various types of movable objects, sensor failures, and environmental conditions through a single integrated system. The modular architecture allows the same core simulation engine to handle different object types and failure modes, reducing complexity compared to dedicated testing systems for each scenario while maintaining comprehensive reliability assessment capabilities.
Data Source
AI summary
A method includes simulating one or more states of a movable object by implementing a movable object model. Each simulated state is associated with simulated state data of the movable object. The method further includes determining one or more sets of simulated sensor data corresponding to the one or more simulated states respectively by implementing a plurality of sensor models, determining environment data of a simulated environment surrounding the movable object by implementing an environment model, providing the one or more sets of simulated sensor data to a movable object controller configured for generating control signals to adjust states of the movable object, and providing the simulated state data and the environment data to a vision simulator configured for visualizing operations of the movable object in the one or more simulated states.