LiDAR Scheduling System for Weather-Resilient Brightness Measurement

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Solution Overview

Problem

3D-LiDAR measurement data, which includes brightness data, can incorrectly detect wet spots as abnormalities due to weather conditions, particularly when the target is wet, leading to false positives.

Innovation Solution

A scheduling system that acquires brightness data and evaluates its difference from reference data collected under fine weather conditions, rescheduling measurements if the difference exceeds a threshold, thereby accounting for weather and reducing false detections.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If brightness data is used to detect abnormalities in 3D-LiDAR measurement data, then abnormality detection capability is improved, but false detection increases due to weather conditions affecting brightness

Engineering Contradiction:

Improveabnormality detection accuracyVSAvoiddetection reliability

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The system performs preliminary actions by acquiring weather information before conducting the measurement, and by pre-processing brightness data to remove weather-related components. This allows the system to anticipate and compensate for weather effects before they interfere with abnormality detection, thereby maintaining both detection accuracy and reliability.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces weather information as an intermediary element that mediates between the brightness data and the abnormality detection process. By using weather information to adjust or filter brightness data, the system eliminates the harmful effect of weather on detection while preserving the useful information for identifying actual abnormalities.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If measurement is conducted outdoors without considering weather, then productivity is improved, but measurement accuracy deteriorates due to wet spots being detected as abnormalities

Engineering Contradiction:

Improvemeasurement efficiencyVSAvoidbrightness data accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system replaces manual weather assessment and measurement rescheduling with an automated system that acquires weather information electronically and algorithmically processes brightness data. This substitution maintains high productivity by eliminating manual intervention while ensuring measurement accuracy through systematic weather compensation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system implements feedback by continuously monitoring weather conditions and using this information to adjust the interpretation of brightness data. The weather information feeds back into the measurement process, allowing the system to dynamically compensate for weather effects and maintain accurate abnormality detection without sacrificing productivity.

Inventive Principle:

Principle #23Feedback

3Measurement precision

If brightness data is acquired and analyzed, then abnormality detection capability is improved, but false positives increase when targets are wet due to reflected light intensity changes

Engineering Contradiction:

Improveabnormality detection capabilityVSAvoidfalse positive detection

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The system converts the harmful effect of weather-induced brightness changes into a beneficial factor by using weather information as a corrective parameter. Instead of treating weather effects as noise to be eliminated, the system uses them as information to adjust the detection threshold or filter the data, thereby converting what was previously harmful into a useful correction mechanism that reduces false positives.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The system effectively reduces the detection of wet spots as abnormalities by considering weather conditions, ensuring accurate data acquisition and minimizing false positives.

Implementation Method 1

brightness data indicating intensity of reflected light of a beam

Methodology Applied

Scientific EffectLight reflection: Reflection

Data Source

PatentUS20230194720A1Scheduling system, scheduling device, scheduling method, and computer readable medium

Publication Date: 2023.06.22 NEC CORP

AI summary

A scheduling system according to the present disclosure includes a measurement unit that acquires at least brightness data indicating intensity of reflected light of a beam by performing measurement, a scheduler that schedules a measurement date on and time at which the measurement unit performs the measurement, and a measurement data evaluation unit that holds in advance reference brightness data, the reference brightness data being the brightness data acquired by the measurement unit in the past when weather was fine, and evaluate whether a difference between the brightness data acquired by the measurement unit and the reference brightness data is greater than or equal to a threshold value. When a result of the evaluation by the measurement data evaluation unit indicates that the difference is greater than or equal to the threshold value, the scheduler reschedules the measurement date on and time at which the measurement unit performs the measurement.