LiDAR Sensor Window Cleaning Delay for Accurate Dirt Detection
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Solution Overview
Problem
Existing sensor systems face challenges in accurately detecting dirt on LiDAR transmissive parts, especially when the vehicle is in motion or stationary, due to erroneous liquid residue and changing landscapes, leading to incorrect dirt determination and wasteful cleaning liquid consumption.
Innovation Solution
A sensor system with a light receiving unit, cleaner, and control unit that delays cleaner actuation after operation completion to prevent erroneous dirt detection, using reflection intensity comparisons and movement history to determine dirt attachment based on predicted positions and intensities, and utilizing vehicle speed and reference information for accurate dirt determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dirt determination is performed immediately after the cleaner operates, then the detection frequency is high and responsiveness is improved, but erroneous determination occurs due to remaining cleaning liquid
Solution Approach 1:
The system performs preliminary cleaning operation and then waits for a predetermined time period before performing dirt determination. This preliminary action of cleaning followed by a time delay ensures that cleaning liquid has evaporated or been removed, preventing erroneous detection. The time delay is a predetermined action taken before the measurement to ensure accurate results.
2Ease of operation
If the sky is used as a detection target, then dirt detection is simplified and consistent results are obtained, but the method fails when traveling in a tunnel where the sky is not visible
Solution Approach 1:
The system uses multiple detection targets including both the sky and ground objects. When the sky is visible, it serves as a detection target; when the vehicle is in a tunnel or the sky is not visible, ground objects automatically serve as alternative detection targets. This multi-functionality ensures the dirt detection system operates reliably across various environments without requiring manual intervention.
Solution Approach 2:
The system dynamically selects detection targets based on environmental conditions. The target selection is not fixed but adapts in real-time: sky regions are used when visible, and ground objects are used when the sky is not visible or during tunnel travel. This dynamic adaptation maintains detection effectiveness across changing conditions.
3Measurement precision
If dirt detection is based on changing landscape, then dirt can be detected when the vehicle is moving, but the method cannot detect dirt when the vehicle is stopped
Solution Approach 1:
The system implements multiple detection modes that work in different vehicle states: motion-based detection using landscape changes when the vehicle is moving, and reflection intensity-based detection when the vehicle is stopped. The system automatically selects the appropriate detection mode based on vehicle motion state, ensuring dirt detection capability across all operating conditions.
4Reliability
If the cleaner is actuated continuously based on erroneous detection, then cleaning is performed frequently, but cleaning liquid is wasted and the cleaner operates unnecessarily
Solution Approach 1:
The system performs a preliminary time delay after cleaning operation before performing dirt determination. This preliminary waiting period allows cleaning liquid to evaporate or be removed, preventing false positive detection results. By delaying the measurement until conditions are appropriate, the system avoids unnecessary re-cleaning and reduces cleaning liquid waste.
Solution Approach 2:
The system uses feedback from multiple detection results over time to control cleaner actuation. Instead of acting on a single detection result, the system considers temporal patterns and multiple measurements, only triggering cleaning when dirt is consistently detected. This feedback mechanism reduces false positives and prevents unnecessary cleaning operations, conserving cleaning liquid.
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 reduces erroneous dirt detection and wasteful cleaning by ensuring accurate dirt determination through delayed cleaner actuation and intelligent dirt detection methods, allowing for efficient cleaning only when necessary.
Implementation Method 1
a light emitting unit configured to emit light to a detection range via a transmissive part configured to transmit light, a light receiving unit configured to receive light emitted from the light emitting unit and reflected by hitting at an object
Implementation Method 2
a cleaner capable of cleaning the transmissive part
Data Source
AI summary
A cleaner for cleaning a transmissive portion of a sensor including a light receiving unit that receives light from a detection target via the transmissive portion is not operated by a cleaner control unit within a predetermined time after the drive of the cleaner is complete.