Autonomous Tractor Path Routing With Aerial Obstacle Updates
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Solution Overview
Problem
Agricultural tasks often require significant labor and time, and existing tractor systems face challenges with path routing due to environmental obstructions that may change or go undetected, necessitating costly on-board equipment or operator intervention.
Innovation Solution
Utilizing aerial images to detect objects and dynamically update path routing for autonomous tractors, combining sensor data to adapt routes in real-time, and optionally involving a remote system for image processing and route determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional tractor systems use basic path routing without advanced detection, then device complexity is reduced, but reliability of path routing deteriorates due to undetected environmental obstructions
Solution Approach 1:
The patent uses aerial images as an intermediary to provide environmental information to the path routing system. Instead of equipping the tractor with complex onboard detection systems, the solution introduces an external aerial imaging system that captures images of the environment, which are then processed to identify obstructions and update paths. This mediator approach improves reliability while avoiding direct complexity in the tractor system.
Solution Approach 2:
The patent transitions from ground-based detection to aerial-based detection, changing the dimensional perspective from which environmental data is collected. By using overhead aerial images instead of ground-level sensors, the system gains a comprehensive view of the environment that improves obstruction detection reliability without requiring complex multi-sensor arrays on the tractor itself.
2Adaptability or versatility
If aerial image processing is used for dynamic path updates, then adaptability to environmental changes is improved, but loss of time for image processing and analysis increases
Solution Approach 1:
The system performs preliminary processing of aerial images to identify potential obstructions and path issues before the tractor reaches those areas. By analyzing images in advance and pre-computing alternative paths, the system reduces the real-time processing burden when dynamic adjustments are needed, thereby maintaining high adaptability while minimizing time loss during critical navigation moments.
Solution Approach 2:
The patent implements a feedback loop where aerial image data is continuously processed and used to update the path routing system. The processed information feeds back into the navigation system, enabling real-time adaptability. This continuous feedback mechanism allows the system to maintain high adaptability while distributing processing loads over time rather than requiring all processing to occur at once.
3Measurement precision
If multiple sensors and onboard equipment are installed on the tractor for obstruction detection, then measurement precision of environmental objects is improved, but device complexity and cost increase
Solution Approach 1:
Instead of placing complex detection sensors on the tractor, the patent uses aerial images as a copy or representation of the physical environment. The aerial imaging system creates a digital replica of the terrain and obstructions, which can be analyzed with high precision without requiring the tractor to carry expensive and complex sensor arrays. This copying approach achieves high measurement precision while keeping the tractor system simple.
4Adaptability or versatility
If manual operator intervention is used for path adjustments, then adaptability to unexpected obstructions is improved, but productivity decreases due to labor intensive operations
Solution Approach 1:
The patent implements an automated system that performs path adjustment functions that would traditionally require manual operator intervention. The aerial image processing system automatically detects obstructions and computes alternative paths, enabling the tractor to self-adjust its route without operator input. This automation maintains the adaptability benefits of manual intervention while eliminating the associated labor requirements, thereby improving productivity.
Data Source
AI summary
A method may include detecting one or more objects within an agricultural environment based on an analysis of a first aerial image of the agricultural environment and determining a first navigational route for an autonomous tractor system to follow to perform an agricultural task within the agricultural environment in view of the detected objects. The autonomous tractor system may be configured to navigate through the agricultural environment via the first navigational route. The method may further include, while autonomous tractor system is navigating through the agricultural environment via the first navigational route, obtaining, from one or more sensors of the autonomous tractor system, data regarding a second object within an agricultural environment. The method may also include determining a second navigational route for the autonomous tractor system to follow to perform the agricultural task within the agricultural environment in view of the first navigational route and the second object.