Earth-Moving Vehicle LiDAR Calibration for Autonomous Control
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Solution Overview
Problem
Existing techniques for autonomous control of powered earth-moving vehicles face challenges such as limited sensed data, inability to perform fully autonomous operations with on-site obstacles, and coordination issues between multiple vehicles, requiring bulky and expensive hardware systems.
Innovation Solution
The implementation of an Earth-Moving Vehicle Autonomous Operations Control (EMVAOC) system that automatically controls the movement of powered earth-moving vehicles, including calibrating on-vehicle sensors based on sensor position and orientation, to perform autonomous operations while ensuring safety and coordinating with multiple vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional autonomous control systems are implemented, then basic autonomous operations can be achieved, but the hardware systems become bulky and expensive
Solution Approach 1:
The patent applies universality by using a single LiDAR sensor to perform multiple functions: primary obstacle detection, calibration target detection, and self-calibration reference. This multi-functional approach eliminates the need for separate calibration hardware and specialized sensors, reducing overall system complexity while maintaining full autonomous operation capability.
Solution Approach 2:
The system implements self-service through automated calibration procedures where the vehicle uses its own LiDAR sensor to detect calibration targets and automatically adjust sensor parameters. The autonomous control system performs self-diagnosis and self-calibration without external intervention, eliminating the need for bulky manual calibration equipment and reducing hardware requirements.
2Device complexity
If limited types of sensed data are used, then system complexity is reduced, but the ability to perform fully autonomous operations is compromised
Solution Approach 1:
The patent applies parameter changes by utilizing a single LiDAR sensor across multiple operational modes and detection parameters. The sensor operates in different measurement modes (distance, velocity, calibration target recognition) and adjusts its detection parameters dynamically based on operational requirements, enabling full autonomous functionality without adding sensor complexity.
Solution Approach 2:
The LiDAR sensor serves universal purposes: it detects obstacles during normal operation, identifies calibration targets during calibration phases, and provides reference data for self-calibration. This multi-functionality allows the system to perform fully autonomous operations with a single sensor type, avoiding the need for multiple specialized sensors.
3Measurement precision
If manual calibration procedures are used, then calibration accuracy can be achieved, but operation time and complexity increase
Solution Approach 1:
The system performs self-calibration automatically using the LiDAR sensor to detect calibration targets and compute correction parameters without human intervention. The autonomous control system executes the calibration procedure autonomously, eliminating time-consuming manual operations while maintaining calibration accuracy through algorithmic processing of sensor data.
Solution Approach 2:
The calibration targets are pre-positioned in the environment before vehicle operation begins. The LiDAR sensor automatically detects these pre-placed targets and uses them for calibration, eliminating the need for time-consuming manual setup and measurement procedures during actual calibration execution.
4Extent of automation
If multiple vehicles operate independently, then individual vehicle autonomy is achieved, but coordination between vehicles becomes problematic
Solution Approach 1:
The patent applies merging by integrating calibration and coordination functions into the existing autonomous control system. The same LiDAR sensor and control architecture used for individual vehicle autonomy are extended to perform inter-vehicle calibration and coordination, eliminating the need for separate dedicated coordination hardware and reducing overall system complexity.
Solution Approach 2:
The autonomous control system performs multiple functions: it controls individual vehicle operations, detects calibration targets for self-calibration, and coordinates with other vehicles using the same sensor suite. This multi-functionality enables both individual autonomy and inter-vehicle coordination without adding specialized coordination hardware.
Data Source
AI summary
Systems and techniques are described for implementing autonomous control of powered earth-moving vehicles, including to automatically calibrate sensors on a powered earth-moving vehicle, such as to determine position and orientation of directional sensors on movable vehicle parts. For example, an on-vehicle sensor to be calibrated may include a LIDAR sensor located on the powered earth-moving vehicle, such as on a movable component part of the vehicle (e.g., a hydraulic arm, a tool attachment, etc.), and a global common frame of reference is determined for different datasets gathered at different times from such a sensor in order to combine or compare the datasets, such as by determining the sensor position in 3D space at a time of dataset gathering (e.g., relative to another reference point on the vehicle with a known location in the global common frame of reference, such as by using one or more determined transforms).