Vehicle LiDAR Self-Calibration for Pitch, Roll, and Yaw Offsets
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Lidar systems in vehicles can become misaligned during service or due to vehicle tilt, introducing unwanted angular offsets in point clouds, which affect accuracy.
Innovation Solution
A lidar self-calibration system that uses the lidar sensor itself to detect and compensate for angular offsets by determining tilt angles and performing compensation based on reference objects, isolating angles into pitch, roll, and yaw, and applying corresponding offsets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If lidar is mounted on a vehicle, then it can perform remote sensing and ranging, but it may become misaligned due to vehicle tilt or service, introducing angular offsets
Solution Approach 1:
The lidar system performs self-calibration by using its own point cloud data to detect reference objects (road surface, curb, building walls) and automatically calculate compensation values for pitch, roll, and yaw angles. The system uses its own sensing capabilities to identify and correct its own misalignment without requiring external calibration equipment or manual intervention.
Solution Approach 2:
The system continuously monitors the vehicle's orientation by comparing detected reference object positions with expected positions, calculates the angular offsets (pitch, roll, yaw), and applies compensation values to correct the point cloud data. This closed-loop feedback mechanism ensures ongoing calibration accuracy.
2Measurement precision
If traditional calibration methods are used, then external equipment is required, but the process becomes complex and time-consuming
Solution Approach 1:
The lidar system performs self-calibration by using its own point cloud data to detect reference objects (road surface, curb, building walls) and automatically calculate compensation values for pitch, roll, and yaw angles. The system uses its own sensing capabilities to identify and correct its own misalignment without requiring external calibration equipment or manual intervention.
Solution Approach 2:
The system uses naturally occurring environmental features (road surface, curb, building walls) as intermediary reference objects for calibration. These common environmental elements serve as mediators between the lidar and the calibration process, eliminating the need for specialized calibration equipment while maintaining accuracy.
3Reliability
If lidar calibration is performed manually, then accuracy can be maintained, but the process requires significant time and resources
Solution Approach 1:
The system performs calibration at periodic intervals based on predetermined conditions such as vehicle mileage, operating time, or specific geographic locations. This automated periodic calibration maintains reliability without requiring continuous manual intervention, significantly reducing time and resource investment while ensuring the lidar remains accurately calibrated.
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 corrects angular offsets in lidar systems, ensuring accurate point cloud data by compensating for pitch, roll, and yaw misalignments, enhancing precision in applications like autonomous navigation.
Implementation Method 1
Lidar (which is an acronym that stands for 'LIght Detection And Ranging') is a remote sensing method that uses light in the form of a pulsed laser to measure ranges or variable distances. Specifically, in the lidar technology, a laser is used for targeting an object, and the ranges or variable distances can be obtained by measuring the time for the reflected light to return to the receiver.
Implementation Method 2
determine a tilt angle of the lidar sensor based on the lidar reference signal; isolating the tilt angle into a plurality of isolated angles, wherein the isolated angles include a pitch, a row and a yaw
Data Source
AI summary
A system and a method for performing perorming lidar self-calibration are provided. The system includes a lidar sensor disposed on a vehicle. In operation, the lidar sensor obtains a lidar reference signal based on a plurality of reference objects corresponding to the vehicle, and determines a tilt angle of the lidar sensor based on the lidar reference signal. The tilt angle is then isolated into multiple isolated angles, such as a pitch, a row and a yaw. For each corresponding isolated angle, the lidar sensor determines, based on a corresponding calibration criteria, a corresponding offset between the lidar sensor and the vehicle for the corresponding isolated angle, and performs a compensation to the corresponding isolated angle based on the corresponding offset. Thus, the lidar sensor may detect and compensate any angular offset to the point cloud, thus achieving lidar self-calibration.