Crewless Aircraft Target-State Estimation for Safe Interaction
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Solution Overview
Problem
Existing crewless aircraft systems face challenges in safely interacting with recognition targets, such as animals or people, due to unpredictable states that may lead to attacks or unsafe interactions.
Innovation Solution
A crewless aircraft equipped with a state estimation unit that analyzes camera images or motor drive signals to determine the state of a recognition target, and an action determination unit that decides the aircraft's actions based on the estimated state, ensuring safe interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a crewless aircraft interacts with a recognition target without state estimation, then the interaction can proceed freely, but the safety of the interaction deteriorates due to unpredictable states of the target
Solution Approach 1:
The state estimation unit performs preliminary assessment of the recognition target's state (emotional state, physical state) before the aircraft executes any interaction actions. This advance estimation allows the aircraft to predict potential safety issues and adjust its behavior proactively, ensuring safe interaction without requiring complex real-time reaction systems
Solution Approach 2:
The system continuously estimates the state of the recognition target based on sensor information (camera images, sensor data) and uses this feedback to dynamically adjust the aircraft's actions. The state estimation unit processes ongoing information about the target's emotional and physical state, creating a closed-loop control system that adapts to changing conditions while maintaining safety
2Measurement precision
If the aircraft uses only instantaneous sensor information to estimate target state, then the processing is simple and fast, but the estimation accuracy deteriorates due to errors in instantaneous measurements
Solution Approach 1:
The system performs preliminary extraction of time-series features from sensor information before final state estimation. By pre-processing the data to extract meaningful temporal patterns and characteristics, the system prepares high-quality input for the estimation algorithm, improving accuracy without requiring excessive computation during critical decision moments
Solution Approach 2:
The state estimation unit continuously processes sensor information over time, maintaining an ongoing estimation of the recognition target's state. This continuous estimation approach allows the system to accumulate data and refine its understanding of the target's emotional and physical state, improving measurement precision through temporal integration while managing computation efficiently
Data Source
AI summary
The present disclosure relates to a crewless aircraft that enable safe interaction with a recognition target. The crewless aircraft includes a state estimation unit that estimates, based on at least one of a camera image shot of the recognition target by a camera or a drive signal of a motor for a flying operation, a state of the recognition target, and an action determination unit that determines an action of the crewless aircraft based on the estimated state of the recognition target.