Excavator Bucket Coordinate Calibration Using LiDAR and Angle Sensors
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Solution Overview
Problem
Existing methods for calibrating the coordinates of a bucket in an excavator, such as direct measurement, manual point selection, and scenario characterization, suffer from low accuracy, labor-intensity, and lack online verification and updating capabilities, especially when the relative positions of sensors change.
Innovation Solution
A method and device using lidar point cloud data and angle sensor data to determine the coordinates of the bucket's middle tooth in both lidar and excavator coordinate systems, employing an implicit shape model and forward kinematics, with a coordinate calibration matrix calculated via RANSAC estimation to ensure accurate and online calibration without external devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct measurement or manual point selection is used for coordinate calibration, then the calibration process is simple to implement, but the calibration accuracy is low and labor-intensive
Solution Approach 1:
The system performs self-calibration by automatically comparing lidar point cloud coordinates with excavator coordinate system coordinates to generate a calibration matrix, eliminating the need for manual measurement and point selection while improving calibration accuracy
Solution Approach 2:
The patent replaces manual mechanical measurement methods with automated coordinate system transformation algorithms, substituting human-operated mechanical calibration with computational geometry-based calibration that achieves higher precision
2Reliability
If traditional calibration methods are used, then the initial calibration can be completed, but online verification and updating capabilities are lacking when sensor positions change
Solution Approach 1:
The system continuously verifies calibration accuracy by comparing transformed coordinates with actual lidar coordinates and updates the calibration matrix when deviations exceed thresholds, providing real-time feedback control that maintains reliability under position changes
Solution Approach 2:
The calibration system transitions from static initial calibration to dynamic online calibration, allowing the calibration matrix to be automatically updated when sensor positions change, ensuring continuous accuracy without requiring complete recalibration
3Measurement precision
If external calibration devices are added to improve accuracy, then calibration precision increases, but device complexity and cost increase
Solution Approach 1:
The system creates a virtual calibration model by generating 3D point clouds from lidar data and transforming them into the excavator coordinate system, using digital copying and transformation rather than physical calibration artifacts to achieve high precision
Solution Approach 2:
The calibration method uses existing lidar and excavator coordinate system data for multiple purposes: initial calibration, online verification, and automatic updating, eliminating the need for dedicated external calibration devices while maintaining high accuracy
Data Source
AI summary
A method for calibrating coordinates of a bucket, a method for updating coordinate calibration, a computer device, a calibration system, a non-transitory computer-readable storage medium and an excavator are provided. The method for calibrating coordinates of a bucket includes: acquiring lidar point cloud data and angle sensor data of the bucket of an excavator; determining coordinates of a middle bucket tooth of the bucket in a lidar coordinate system according to the lidar point cloud data of the bucket; determining the coordinates of the middle bucket tooth of the bucket in an excavator coordinate system according to the angle sensor data of the bucket; and determining a coordinate calibration matrix according to the coordinates of the middle bucket tooth of the bucket in the lidar coordinate system and in the excavator coordinate system.