Aerial Vehicle Object Avoidance Using Object and Retreat Vectors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automated aerial vehicles (AAVs) face challenges in autonomously avoiding collisions with other objects without human intervention, as existing methods require complex surroundings analysis and object intent determination, which can be inefficient and prone to prediction by malicious objects.
Innovation Solution
The AAV employs multiple rangefinders to determine object vectors, retreat vectors, and defensive directions, generating an avoidance maneuver by combining these elements, and communicates with other AAVs to share avoidance information and adapt to successful strategies, allowing for quick and unpredictable avoidance maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex surroundings analysis and object intent determination are used, then collision avoidance capability is improved, but system complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential information needed for collision avoidance (object position, velocity, and basic classification) while discarding complex analysis of object intent and detailed surroundings. This is achieved through the object classification module that categorizes objects into simple types (avian, mammal, UAV, etc.) based on basic sensor data, eliminating the need for complex intent determination while maintaining effective avoidance capability
Solution Approach 2:
Instead of analyzing object intent to determine avoidance strategy, the patent inverts the approach by using the classified object type to directly select from pre-defined avoidance maneuvers. The system doesn't try to understand what the object wants to do, but rather what maneuver is most effective based on object classification, thereby reducing computational complexity while maintaining reliability
2Reliability
If complex surroundings analysis and object intent determination are used, then collision avoidance capability is improved, but processing speed deteriorates
Solution Approach 1:
The patent performs preliminary classification of objects into categories (avian, mammal, UAV, etc.) based on basic sensor data before detailed avoidance maneuver selection. This pre-processing step organizes information in advance, allowing the system to quickly select appropriate avoidance maneuvers without performing complex real-time analysis, thereby improving processing speed while maintaining avoidance capability
Solution Approach 2:
The system performs only the necessary level of analysis - classifying objects into broad categories rather than fully analyzing their intent and detailed characteristics. This partial action approach provides sufficient information for effective avoidance without the computational overhead of complete surroundings analysis, achieving a balance between reliability and processing speed
3Ease of operation
If predictable avoidance maneuvers are used, then ease of operation is improved, but safety against malicious objects deteriorates
Solution Approach 1:
The patent implements dynamic selection of avoidance maneuvers based on real-time object classification and environmental factors. Rather than using fixed predictable patterns, the system adapts its avoidance strategy by selecting from multiple maneuver options (climb, turn, dive, etc.) based on the classified object type and current flight conditions, making it difficult for malicious objects to predict the AAV's response while maintaining operational effectiveness
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
This approach enables AAVs to efficiently and effectively navigate around obstacles without complex surroundings analysis, reducing the risk of collisions and making it difficult for malicious objects to predict avoidance maneuvers, thereby enhancing safety and operational efficiency.
Implementation Method 1
detecting a presence of an object; determining an object vector representative of a distance and a direction of the object
Data Source
Figure 1
Figure 2A~2C
Figure 3A~3C
AI summary
This disclosure describes an automated aerial vehicle that includes one or more object detection elements configured to detect the presence of objects and an avoidance determining element configured to cause the automated aerial vehicle to automatically determine and execute an avoidance maneuver to avoid the objects. For example, an object may be detected and an avoidance maneuver determined based on a position of the object and an object vector representative of a direction and a magnitude of velocity of the obj ect.