Vehicle Trajectory Replanning via Grid Repulsion Signals
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Solution Overview
Problem
In mixed-use airspace, piloted and unpiloted vehicles face challenges in safely avoiding obstacles and maintaining safe distances, especially when obstacles are moving, requiring dynamic re-computation of flight paths in real-time.
Innovation Solution
A system and method for continuously re-planning a vehicle's trajectory by modeling an area into sub-areas, associating parameters, modifying summation values based on proximity, and identifying optimal paths that avoid obstacles through repulsion and attraction signals, allowing for real-time dynamic path adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time dynamic path re-computation is implemented to avoid moving obstacles, then safety and reliability of obstacle avoidance is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent divides the continuous path planning problem into discrete grid cells or spatial segments. Each cell is evaluated independently for obstacle presence and path validity, allowing parallel processing and reducing overall computational complexity while maintaining safety through comprehensive coverage of the search space.
Solution Approach 2:
The system pre-computes and stores obstacle data, grid representations, and path evaluation criteria before real-time operation. This preliminary preparation enables faster real-time re-computation by avoiding redundant calculations and focusing computational resources only on dynamic path adjustments rather than complete path planning from scratch.
2Reliability
If continuous monitoring and dynamic re-computation of flight paths is performed to maintain safe separation from other vehicles, then safety and reliability are improved, but loss of time and computational resources increase
Solution Approach 1:
The patent implements periodic monitoring and re-computation cycles at optimized intervals rather than continuous processing. The system evaluates when re-computation is necessary based on changes in obstacle positions, vehicle dynamics, or path deviation thresholds, reducing unnecessary computational cycles while maintaining safety through timely updates.
Solution Approach 2:
The system continuously monitors actual vehicle positions, obstacle movements, and path deviations, using this feedback to trigger selective re-computation only when safety margins are compromised or significant changes occur. This feedback-driven approach minimizes redundant calculations while ensuring safe separation is maintained through responsive path adjustments.
3Adaptability or versatility
If complex path re-planning algorithms are used to handle mixed-use airspace with multiple moving obstacles, then adaptability and obstacle avoidance capability are improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent employs dynamic path re-planning algorithms that adapt their complexity and search depth based on the number of obstacles, their movement patterns, and the urgency of avoidance requirements. The system transitions between simplified and complex algorithmic approaches depending on the operational context, maintaining high adaptability while managing computational complexity through conditional algorithm selection.
Data Source
AI summary
A method and system for continuously re-planning a vehicle's path, in the face of stationary and moving obstacles, dynamically calculates a new path in real time which is both efficient and maintains minimum safety clearances relative to obstacles. Repulsion signals emanating from obstacles and propagating through delineated sections of a grid representing a geographic space are summed along with values representing the relative distance of the sections from the vehicle origin and vehicle destination. The grid sections having optimal values according to a predetermined criteria represent an efficient and safe travel path between the vehicle origin and destination.