Vehicle Automated Unloading With Dynamic Fill Model Control
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Solution Overview
Problem
The unloading of crop material into a transport vehicle is challenging due to the need for automation and efficient management of fill characteristics, which existing systems fail to address effectively, especially under varying conditions and external interference.
Innovation Solution
A system utilizing a fill model that predicts and adjusts unloading parameters based on variables such as material type, moisture content, and vibration, combined with a perception system for real-time adjustments, ensures accurate and efficient unloading by dynamically updating the fill model with perception data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a fill model is used to control unloading operation, then automation level increases, but system complexity increases
Solution Approach 1:
The fill model is developed and calibrated in advance using historical unloading data, material properties, and container characteristics. This preliminary action creates a predictive framework that automatically estimates fill state without requiring real-time complex sensing, thereby increasing automation while managing system complexity through pre-computed models.
Solution Approach 2:
Instead of directly measuring the complex three-dimensional fill state of the container, the system creates a simplified digital copy or representation of the fill model. This abstracted model captures essential fill characteristics without requiring complex physical sensors, enabling automated control while reducing measurement and system complexity.
2Measurement precision
If perception system is used to detect fill state, then measurement precision improves, but reliability decreases under external conditions
Solution Approach 1:
The system implements feedback by comparing the fill model predictions with actual unloading parameters and outcomes. This feedback loop allows the system to continuously refine and update the fill model, improving measurement precision over time while enhancing reliability through adaptive learning that compensates for external condition variations.
Solution Approach 2:
The fill model incorporates multiple variables including material properties (moisture content, particle size), unloading parameters (rate, duration, location), and environmental conditions. By changing and adjusting these parameters dynamically, the system maintains measurement precision and reliability across varying external conditions rather than relying on a single fixed detection method.
3Productivity
If unloading operation is automated, then productivity increases, but ease of operation decreases
Solution Approach 1:
The fill model operates autonomously by automatically estimating fill state, predicting overflow conditions, and recommending unloading parameter adjustments without requiring continuous operator intervention. This self-service capability increases productivity while the simplified user interface and automated decision-making actually improve ease of operation by reducing the cognitive load and manual tasks required.
4Manufacturing precision
If multiple variables are considered in fill model, then manufacturing precision improves, but device complexity increases
Solution Approach 1:
The fill model is segmented into distinct functional modules: material property characterization, unloading parameter tracking, fill state estimation, and overflow prediction. Each module processes specific variables independently, allowing the system to consider multiple factors for precise fill control while managing complexity through modular architecture that enables independent development and calibration of each segment.
Data Source
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AI summary
A vehicle automated unloading system (200, 1000, 1100, 1200) may include a fill model (220) and an unloading controller (224, 1024). The fill model (220) is a model of a fill characteristic of a container (85) as a function of variables comprising material unloading times, material unloading rates and material unloading locations. The unloading controller (224, 1024) is to (a) determine a current model-based fill characteristic of the container using the dynamic fill model and (b) output control signals to adjust at least one of a material unloading time, a material unloading rate and a material unloading location based upon the current model-based fill characteristic of the container (85).