Warning Device Adjusts Anticipation Area Based on Person Wobble
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Solution Overview
Problem
Conventional warning devices in environments like rooms and construction sites suffer from frequent erroneous warnings due to the unpredictable placement of objects, leading to reduced reliability.
Innovation Solution
A warning system that estimates movement information and anticipation areas for individuals using vicinity and person sensors, adjusts these areas based on the condition and wobble level of the person, and determines if obstacles are warning objects, thereby issuing warnings with higher reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the warning device uses a simple detection system to monitor objects and persons, then the device complexity is reduced, but the reliability of warnings decreases due to frequent erroneous warnings in environments with disordered objects
Solution Approach 1:
The detection system is segmented into multiple specialized sensors: vicinity sensors for detecting objects in the surrounding area, person sensors for detecting person-specific information, and movement sensors for tracking motion. This segmentation allows each sensor type to focus on specific aspects of the environment, improving overall detection accuracy and warning reliability without requiring a single overly complex detection system
Solution Approach 2:
The system estimates a three-dimensional movement anticipation area based on movement information, adding spatial dimensionality to the warning process. By calculating the anticipated position, moving direction, and moving speed to define a volumetric anticipation area, the system can more accurately distinguish between actual threats and benign objects, reducing false warnings while maintaining manageable complexity
2Reliability
If the warning device monitors all objects in the environment, then the coverage is comprehensive, but the number of false warnings increases due to objects placed in disorder
Solution Approach 1:
The system dynamically adjusts the movement anticipation area based on real-time movement information and person-specific conditions. The anticipation area is not fixed but adapts to the person's actual movement pattern, allowing the system to focus monitoring resources on relevant areas and reduce false warnings from static or irrelevant objects in the environment
Solution Approach 2:
The movement anticipation area serves as an intermediary between the detected objects and the warning decision. Instead of directly warning about all detected objects, the system first determines whether objects fall within the dynamically calculated anticipation area, acting as a filter that reduces the number of objects requiring full monitoring while maintaining warning accuracy
3Reliability
If the warning device issues warnings for all detected obstacles, then the safety coverage is maximized, but the frequency of erroneous warnings increases in environments with disordered objects
Solution Approach 1:
The system uses feedback from multiple sensor inputs (vicinity sensor, person sensor, movement sensor) to continuously refine the movement anticipation area and object detection. This multi-source feedback mechanism allows the system to distinguish between legitimate warnings and false alarms by cross-validating information from different sensors before issuing warnings, improving warning validity while maintaining efficient operation
Data Source
AI summary
A warning device includes a person position estimation unit, a movement anticipation unit that estimates a movement anticipation area based on the movement information, a vicinal situation provision unit that provides vicinal situation information including a position of an obstacle, based on at least one of the first detection signal and map information, a condition estimation unit that estimates condition of the object person based on a second detection signal outputted from a person sensor, and a risk estimation unit that outputs a warning signal when the obstacle is judged to be a warning object based on the vicinal situation information, the movement anticipation area, and the condition of the object person. The movement anticipation unit adjusts the movement anticipation area based on the condition of the object person.