Virtual Safety Bubbles for Autonomous Farm Machine Navigation
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Solution Overview
Problem
Farming machines face challenges in navigating confined or dense environments due to their large size, which makes it difficult to gauge the proximity of objects, leading to slow and cautious operation.
Innovation Solution
A farming machine is configured with a detection system and a control system to generate and maintain a virtual safety bubble, allowing the machine to autonomously perform farming actions while avoiding obstacles by dynamically adjusting the bubble based on configuration changes and obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If farming machines operate at high speed in confined or dense environments, then productivity increases, but collision risk with objects increases due to difficulty in gauging proximity
Solution Approach 1:
The system performs preliminary detection of objects in the environment using detection mechanisms (cameras, sensors) before the farming machine reaches them. The control system calculates safe operating speeds based on detected objects and establishes virtual safety bubbles in advance, allowing the machine to maintain higher speeds while still avoiding collisions by having safety parameters pre-determined based on environmental conditions.
2Reliability
If farming machines move slowly and cautiously to avoid objects, then collision risk decreases, but productivity reduces due to reduced operating speed
Solution Approach 1:
The control system dynamically adjusts the virtual safety bubble parameters and safe operating speed in real-time based on the farming machine's current configuration, detected objects, and environmental conditions. When the machine switches between different configurations or detects new objects, the safety bubble and speed limits are automatically updated, allowing the machine to operate at optimal speeds for each situation rather than maintaining a consistently slow cautious pace.
3Reliability
If the virtual safety bubble is enlarged to increase safety margin, then collision avoidance improves, but the area available for farming operations decreases
Solution Approach 1:
The control system creates different virtual safety bubble configurations based on the farming machine's current operations and environment. Instead of using a uniform large safety bubble in all situations, the system adjusts the bubble size and shape locally according to specific conditions - enlarging the safety margin only in directions or areas where objects are detected or where the machine configuration requires it, while maintaining smaller bubbles in clear areas to maximize farming coverage.
Data Source
AI summary
An autonomous farming machine navigable in an environment for performing farming action(s) is disclosed. The farming machine receives a notification from a manager that there are no obstacles in the blind spots of the detection system. The farming machine applies an obstacle detection model to the captured images to verify that there are no obstacles in unobstructed views. The farming machine determines a configuration of the farming machine. The farming machine determines a virtual safety bubble for the farming machine to autonomously perform the farming action(s) based on the determined configuration. The farming machine detects an obstacle in the environment by applying the obstacle detection model to the captured images. The farming machine determines that the obstacle is entering the virtual safety bubble. In response to determining that the obstacle is entering the virtual safety bubble, the farming machine terminates operation of the farming machine and/or enacts preventive measures.