Unmanned Vehicle Path Deviation Threshold Control
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Solution Overview
Problem
Unmanned vehicles face collisions due to lack of geographic information about obstacles and unpredictable environmental conditions, leading to deviations from planned paths, which can result in inefficient path recalculations and potential collisions with other vehicles or obstacles.
Innovation Solution
Implementing a system where unmanned vehicles determine their current and planned positions, calculate deviations, and adjust their movement based on predetermined thresholds to decide when to recalculate a new path, thereby reducing unnecessary path recalculations and maintaining efficient navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If unmanned vehicles frequently recalculate paths in response to deviations, then collision avoidance capability is improved, but processing resource consumption increases and system efficiency deteriorates
Solution Approach 1:
The system changes the parameter of path recalculation frequency by introducing a threshold-based decision mechanism. Instead of recalculating paths frequently or continuously, the system monitors deviation magnitude and only triggers recalculation when deviation exceeds a predetermined threshold, thereby optimizing the balance between collision avoidance and processing efficiency
Solution Approach 2:
The system implements feedback by continuously monitoring the deviation between current position and planned path, comparing it against a threshold, and using this feedback to decide whether to recalculate the path. This closed-loop control ensures recalculation occurs only when necessary, avoiding unnecessary processing while maintaining safety
2Measurement precision
If unmanned vehicles recalculate paths for minor deviations, then navigation accuracy is improved, but time consumption increases
Solution Approach 1:
The system changes the parameter of navigation intervention by introducing a threshold for deviation magnitude. Minor deviations below the threshold are allowed to persist without triggering path recalculation, while only significant deviations trigger the time-consuming recalculation process, thereby optimizing the trade-off between navigation accuracy and time consumption
3Productivity
If unmanned vehicles maintain planned paths during minor deviations, then processing resource efficiency is improved, but collision risk increases
Solution Approach 1:
The system uses feedback monitoring of deviation magnitude to decide when to maintain the planned path and when to recalculate. By continuously measuring deviation and comparing it to a threshold, the system ensures that path maintenance (which conserves processing resources) occurs only when it is safe to do so, while triggering recalculation when collision risk becomes significant
4Adaptability or versatility
If unmanned vehicles in a fleet independently recalculate paths, then individual vehicle adaptability is improved, but coordination difficulty increases
Solution Approach 1:
The system changes the parameter of path adjustment behavior by using a unified threshold parameter across the fleet. Each vehicle independently monitors its own deviation and applies the same threshold-based recalculation logic, which provides individual adaptability while maintaining coordination through parameter consistency across all vehicles
Data Source
AI summary
Some embodiments are directed to an unmanned vehicle. The unmanned vehicle can include a memory unit that is configured to store a planned path of the unmanned vehicle. The unmanned vehicle can also include a position unit that is configured to determine a current position of the unmanned vehicle, the position unit further configured to determine a planned position of the unmanned vehicle based on the planned path data stored in the memory unit. The unmanned vehicle can further include a control unit disposed in communication with the position unit, the control unit configured to determine a deviation based on the planned position and the current position of the unmanned vehicle, and control a movement of the unmanned vehicle such that the unmanned vehicle moves along the planned path if the deviation is less than a predetermined threshold.