Autonomous Vehicle Bump Detection and Velocity Control
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Solution Overview
Problem
Autonomous agricultural vehicles face challenges in detecting undetected ruts and obstacles in terrains, leading to potential vehicle maintenance issues and loss of control due to hidden bumps and adverse conditions covered by crops.
Innovation Solution
An autonomous system that uses sensors on the vehicle to detect bumps, transmit data to a base station for map marking and velocity modification, allowing the vehicle to adjust its speed and route based on proximity, current velocity, and bump severity, thereby reducing the impact of obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the autonomous vehicle drives at normal operating velocities through the field, then productivity is improved, but the risk of vehicle damage and loss of control increases due to undetected ruts and obstacles
Solution Approach 1:
The system performs preliminary detection of ruts and obstacles by analyzing sensor data (accelerometers, gyroscopes, depth sensors) before the vehicle reaches problematic areas. The base station processes this data to identify hazardous locations and sends advance warnings to the vehicle controller, allowing the vehicle to maintain normal velocity while being prepared to slow down or adjust its path when approaching detected ruts or obstacles
Solution Approach 2:
The system continuously monitors vehicle acceleration and terrain conditions using onboard sensors, feeds this data to the base station for analysis, and receives feedback in the form of velocity adjustments or route modifications. This closed-loop feedback system enables the vehicle to adapt its operating velocity in real-time based on actual terrain conditions, maintaining both productivity and safety
2Measurement precision
If sensors are used to detect bumps and obstacles, then measurement precision is improved, but device complexity increases due to additional sensors and processing requirements
Solution Approach 1:
The system uses multi-functional sensors already present on the autonomous vehicle for other purposes (accelerometers for vehicle dynamics control, gyroscopes for navigation, depth sensors for crop monitoring) and repurposes them for rut and obstacle detection. This approach improves measurement precision for bump detection without significantly increasing device complexity, as the same hardware serves multiple functions
Solution Approach 2:
The base station acts as an intermediary that performs the complex data processing and analysis functions. Rather than requiring the vehicle to have sophisticated onboard processing capabilities, the base station receives raw sensor data, analyzes terrain conditions, identifies ruts and obstacles, and sends back simplified control commands. This distributes system complexity from the vehicle to the base station infrastructure
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
The system effectively reduces the risk of vehicle damage and loss of control by continuously updating terrain maps with bump data, allowing for precise speed adjustments and route modifications to navigate around severe obstacles, enhancing operational safety and efficiency.
Implementation Method 1
The agricultural vehicle includes a sensor configured to detect the acceleration
Data Source
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AI summary
In one embodiment, a control system for a base station (52) includes a transceiver configured to receive a first signal and send a second signal to an agricultural vehicle (16). The first signal indicates at least an acceleration of the vehicle, a current velocity of the vehicle, and a location relative to a terrain (12) where the vehicle experienced the acceleration, and the second signal indicates a vehicle target velocity. The control system includes a controller configured to determine a bump severity value based on the acceleration and the current velocity of the vehicle, mark an area (14) indicative of the bump on a map (10,30) of the terrain (12) when the bump severity value exceeds a threshold, and automatically generate the second signal when the vehicle enters the area (14). The target velocity is based on a proximity of the vehicle to the bump, the bump severity value, or some combination thereof.