Modular Edge Sensor Calibration for Agricultural Vehicle Mounting
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Solution Overview
Problem
Agricultural robots and rovers face challenges with scalability due to high costs and limited adaptability to unpredictable conditions, and positioning and calibration of sensor-equipped modular edge computing devices on conventional farm equipment can be complex for non-experts.
Innovation Solution
Implementations for automatically determining extrinsic parameters of modular edge computing devices using contactless sensors, such as vision sensors and time-of-flight sensors, to facilitate commissioning, configuration, and calibration, allowing for self-adjustment and real-time orientation and positioning on agricultural vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If modular edge computing devices are mounted on agricultural vehicles to improve flexibility and adaptability, then the adaptability and versatility of the system is improved, but the complexity of positioning, commissioning, and calibration increases
Solution Approach 1:
The system employs self-calibration capabilities where the modular edge computing devices automatically determine their own extrinsic parameters (position and orientation) using contactless sensors to detect fiducial markers on neighboring devices. This self-service approach eliminates the need for manual positioning and calibration by experts, allowing non-expert personnel to deploy devices flexibly on agricultural vehicles without complex setup procedures.
2Measurement precision
If manual positioning and calibration methods are used for modular edge computing devices, then measurement precision can be achieved, but the ease of operation deteriorates due to requiring expert knowledge
Solution Approach 1:
The system incorporates pre-configured fiducial markers on each modular edge computing device that encode identification and configuration information. Before deployment, devices are pre-prepared with these markers and self-identification capabilities. During installation, the automatic detection and calibration processes leverage these pre-configured elements to achieve precise positioning without requiring expert operators to perform complex manual calibration procedures.
3Reliability
If expert personnel are used for commissioning and calibration to maintain measurement precision, then the reliability of calibration is improved, but the productivity decreases due to limited availability of experts
Solution Approach 1:
The automatic calibration system using contactless sensors and fiducial markers enables non-expert personnel to commission and calibrate modular edge computing devices with expert-level precision. The system automatically detects devices, determines their positions and orientations, and configures them correctly without requiring specialized knowledge, thereby significantly increasing productivity while maintaining reliability through automated precision calibration processes.
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
Enables efficient and adaptable deployment of modular edge computing devices on agricultural vehicles, enhancing scalability and flexibility in agricultural operations by simplifying installation and ensuring accurate sensor data capture.
Implementation Method 1
one or more of the contactless sensors comprises a laser. In various implementations, the method may further include: generating one or more instructions to alter an orientation or position of the given modular edge computing device
Data Source
AI summary
Implementations are disclosed for automatic commissioning, configuring, calibrating, and/or coordinating sensor-equipped modular edge computing devices that are mountable on agricultural vehicles. In various implementations, neighbor modular edge computing device(s) that are mounted on a vehicle nearest a given modular edge computing device may be detected based on sensor signal(s) generated by contactless sensor(s) of the given modular edge computing device. Based on the detected neighbor modular edge computing device(s), an ordinal position of the given modular edge computing device may be determined relative to a plurality of modular edge computing devices mounted on the agricultural vehicle. Based on the sensor signal(s), distance(s) to the neighbor modular edge computing device(s) may be determined. Extrinsic parameters of the given modular edge computing device may be determined based on the ordinal position of the given modular edge computing device and the distance(s).