UAV Sensing for Worksites: Real-Time Operation Adjustment
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Solution Overview
Problem
Current worksite operations lack efficient data collection and real-time control mechanisms to optimize the performance of mobile machines, such as agricultural or construction machines, as they operate, leading to potential inefficiencies and inaccuracies in tasks like crop care or chemical application.
Innovation Solution
A system comprising a mobile machine equipped with a controllable mechanism and a communication system that utilizes an unmanned aerial vehicle (UAV) to gather attribute data and effect data, generating a difference map to adjust operations based on the comparison, allowing for real-time control and optimization of tasks like chemical application or crop care.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If remote images are captured by aircraft or satellite platforms to sense field attributes, then measurement coverage is improved, but measurement precision and real-time control capability deteriorate
Solution Approach 1:
The system transitions from ground-based or remote sensing to aerial dimension by deploying UAVs that fly over the field. This dimensional change enables both wide coverage and high-resolution sensing simultaneously, as the UAVs can capture detailed attribute data (precision) across large areas (coverage) from an elevated perspective.
Solution Approach 2:
The patent introduces UAVs as intermediary platforms between traditional remote sensing and ground-based sensing. These UAVs act as mobile sensing nodes that bridge the gap by providing aerial perspective with close-proximity measurement capability, enabling both wide coverage and high precision through their flexible positioning.
2Measurement precision
If ground-based cameras are used to capture field images, then measurement precision is improved, but measurement coverage and productivity deteriorate
Solution Approach 1:
The system replaces static ground-based cameras with dynamic UAVs that can move freely over the field. This dynamic capability allows the sensing platform to cover the entire field area efficiently while maintaining close-proximity high-resolution imaging, thus improving both productivity and measurement precision simultaneously.
Solution Approach 2:
By moving the sensing platform to the aerial dimension, the system achieves both wide coverage and high precision. The UAVs can systematically traverse the field from above, capturing detailed attribute data across the entire area without the coverage limitations of ground-based cameras.
3Device complexity
If traditional sensing systems are used without real-time feedback, then device complexity is reduced, but manufacturing precision and operational accuracy deteriorate
Solution Approach 1:
The system implements a closed-loop feedback mechanism where attribute data collected by UAVs is transmitted to the mobile machine's controller in real-time. This feedback enables the controller to adjust machine operations dynamically, improving operational precision and accuracy while managing system complexity through integrated control architecture.
Data Source
AI summary
A mobile machine includes controllable mechanism that performs a prescribed operation on a worksite as the mobile machine travels over the worksite in a direction of travel, and a communication system that receives attribute data indicative of an attribute corresponding to the worksite, and that receives effect data indicative of an effect of the prescribed operation being performed on the worksite. The mobile machine may further include a control system that generates a difference map indicative of a difference between the attribute data and the effect data, and that controls the controllable mechanism to adjust performance of the prescribed operation on the worksite, based on the difference.