Aircraft Guidance Instructions Using Potential Fields for Obstacle Avoidance
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Solution Overview
Problem
Current aircraft obstacle avoidance systems either rely on collaborative or operator-dependent methods, which are inadequate in complex or unknown environments, leading to potential human error and limited effectiveness in identifying temporary or unforeseen obstacles.
Innovation Solution
An electronic generation system that processes data from various sensors to generate guidance instructions for aircraft, using primitive potential fields to calculate resulting vectors, reducing computing power requirements and pilot cognitive load, and enabling automatic obstacle avoidance maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If operator-dependent methods are used for obstacle avoidance, then the aircraft can adapt to complex environments, but human error and limited analytical capacity increase risk
Solution Approach 1:
The aircraft system autonomously processes sensor data and generates avoidance maneuvers without requiring human analysis or decision-making. The electronic generation system automatically determines obstacle positions, calculates avoidance paths, and executes maneuvers, making the system self-sufficient in complex environments while eliminating human error risks.
Solution Approach 2:
The patent replaces the human operator's cognitive and decision-making system with an electronic generation system that uses sensor data processing and automated calculation algorithms. This substitution transforms the mechanical human-pilot interface into an automated electronic system that reliably processes environmental data and generates avoidance commands without human intervention.
2Measurement precision
If traditional image recognition algorithms are used to process sensor data, then obstacle detection accuracy improves, but computing power requirements increase significantly
Solution Approach 1:
The patent extracts only the essential geometric and positional information from sensor data that is necessary for obstacle avoidance, rather than processing complete images or complex visual data. By taking out only the critical parameters needed for navigation safety, the system achieves adequate detection accuracy with significantly reduced computing power requirements.
Solution Approach 2:
The system performs partial processing of sensor data, focusing only on the portions and parameters that are sufficient for obstacle detection and avoidance maneuvers. Rather than analyzing all sensor data in detail, the electronic generation system processes only the necessary elements to generate safe navigation paths, reducing computational load while maintaining adequate accuracy for safety-critical functions.
3Reliability
If collaborative systems like TCAS or TAWS are used, then obstacle warning capability is provided, but the aircraft cannot evolve in unplanned spaces or identify temporary obstacles
Solution Approach 1:
The electronic generation system dynamically adapts to changing environmental conditions and unplanned situations by continuously processing real-time sensor data. Unlike static collaborative systems with fixed databases, this system can identify and respond to temporary obstacles and unforeseen conditions, dynamically generating appropriate avoidance maneuvers for any situation encountered during flight.
Solution Approach 2:
The system continuously monitors the environment using sensors and prepares avoidance maneuvers in advance by maintaining readiness to process obstacle data and generate escape paths. This preliminary action ensures that when temporary or unplanned obstacles appear, the system can immediately respond with pre-computed avoidance strategies without waiting for database lookups or external system responses.
Data Source
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AI summary
This method of generating at least one aircraft guidance instruction is implemented by an electronic generation system and comprises: - acquisition (100) of data from at least one source, each respective source being chosen from a sensor equipping the aircraft and a database; - determination (110), for each respective source, of at least one potential primitive from the data acquired for said source, each potential primitive generating a potential field applicable to the aircraft; - calculation (120), for each respective source and from the potential primitive(s) determined for said source, of an elementary resultant vector applied to the aircraft; - obtaining (130) an overall resultant vector from a sum of the calculated elementary resultant vector(s); and - conversion (140) of the overall resultant vector into at least one guidance instruction.