LiDAR Sensor Testing via Bar Intersection Analysis
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Solution Overview
Problem
Autonomous Ground Vehicles (AGVs) face navigation errors due to uncertainties in LiDAR sensor data caused by obstructions such as snowflakes, water droplets, and tree leaves, which conventional techniques fail to handle effectively, especially in detecting abrupt sensor failures and anomalies.
Innovation Solution
A method and system for testing LiDAR sensors by radiating a plurality of LiDAR rays and determining intersection points with bars positioned at predetermined distances, computing operational parameters, and determining test results to assess sensor accuracy and detect potential obstructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional techniques use multiple sensors and probabilistic driving models to detect runtime difficulties, then detection capability is improved, but the process becomes lengthy and complex
Solution Approach 1:
The patent extracts the testing function from complex multi-sensor systems and implements it using a simple bar structure. The bar is positioned in the LiDAR sensor's field of view to create detectable obstacles, allowing runtime difficulty detection to be performed by a single sensor through geometric intersection analysis, eliminating the need for multiple sensors and probabilistic models.
Solution Approach 2:
The patent changes the testing approach from probabilistic analysis of multiple sensor inputs to deterministic geometric parameter analysis. By calculating intersection points between LiDAR rays and the known bar geometry, the system achieves rapid, precise detection of sensor malfunctions without time-consuming probabilistic computations.
2Ease of operation
If conventional techniques rely on LiDAR data assuming it is always accurate, then ease of operation is improved, but the ability to detect anomalies is lost
Solution Approach 1:
The patent implements preliminary action by pre-positioning a bar with known geometry in the LiDAR sensor's field of view before operation begins. This predetermined reference object enables the system to continuously verify sensor accuracy through geometric intersection calculations, allowing anomaly detection to be built into the normal operation without complicating the control process.
3Adaptability or versatility
If LiDAR sensor is used for AGV navigation, then navigation capability is improved, but vulnerability to environmental obstructions increases
Solution Approach 1:
The patent introduces a bar as an intermediary reference object between the LiDAR sensor and the environment. This mediator provides a known geometric structure that the sensor can use to continuously calibrate and verify its own performance, creating a reference frame that is immune to environmental conditions like snow, rain, or fog that affect external navigation targets.
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 dynamically monitors LiDAR sensor performance, quickly identifying misalignments or blockages, thereby enhancing navigation reliability and safety by minimizing the impact of environmental factors on sensor accuracy.
Implementation Method 1
Light Detection and Ranging (LiDAR) technology finds implementation across multiple technology domains for various purposes
Data Source
AI summary
A system and method for testing a Light Detection and Ranging (LiDAR) sensor is disclosed. The system includes the LiDAR sensor radiating a plurality of LiDAR rays, a plurality of bars positioned at a predetermined distance from the LiDAR sensor, and a testing device. The method includes triggering a LiDAR sensor to radiate a plurality of LiDAR rays. The method further includes determining at least one intersection point at each of a plurality of bars upon intersection of at least one LiDAR ray from the plurality of LiDAR rays with each of the plurality of bars. The method further includes computing at least one operational parameter for the LiDAR sensor based on the intersection points, and determining one or more test results based on the one or more operational parameters.