Autonomous Vehicle Obstacle Avoidance Without Imaging
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Solution Overview
Problem
Current navigation systems for unmanned aerial vehicles (UAVs) that rely on imaging systems for obstacle detection are expensive and heavy, making them impractical for commercial and recreational use due to the high computational and storage requirements for processing images in real time.
Innovation Solution
The Object Sense and Avoid (OSA) system uses a sensor array to detect objects without imaging, dynamically generating a travel path to avoid obstacles by triangulating object locations and planning a route that minimizes distance while maintaining clearance, utilizing a path planner system and sensor data to determine the next travel direction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If imaging systems are used for obstacle detection, then obstacle detection capability is improved, but weight and cost increase significantly
Solution Approach 1:
The patent replaces imaging systems with acoustic sensor arrays that detect obstacles through sound waves and triangulation. This substitution eliminates cameras, image processors, and associated computational hardware, dramatically reducing weight while maintaining obstacle detection capability through acoustic signal processing instead of optical imaging.
Solution Approach 2:
The patent extracts and removes the imaging subsystem (cameras, image processors, storage systems) from the navigation system, retaining only the essential obstacle detection function through acoustic sensors. This extraction eliminates the heavy computational and storage resources required for image processing while preserving the core navigation safety function.
2Reliability
If imaging systems are used for obstacle detection, then obstacle detection capability is improved, but cost increases due to computational and storage resources
Solution Approach 1:
The patent substitutes acoustic sensor arrays with imaging systems, replacing expensive cameras, high-end processors, and large storage systems with relatively inexpensive acoustic sensors and simple triangulation algorithms. This substitution dramatically reduces computational and storage resource requirements, making the system economically viable for commercial and recreational UAVs.
Solution Approach 2:
The patent employs inexpensive acoustic sensors and simple signal processing algorithms instead of expensive imaging systems. The acoustic sensor array and triangulation method provide a cost-effective solution that eliminates the need for high-end processing systems and large storage capacities, reducing overall system cost while maintaining functional effectiveness.
3Measurement precision
If image processing is performed in real time, then obstacle detection accuracy is improved, but computational resources and processing time increase
Solution Approach 1:
The patent replaces complex image processing systems with acoustic triangulation methodology. Instead of processing visual data through sophisticated algorithms and hardware, the system uses sound wave triangulation which requires minimal computational resources while providing sufficient obstacle detection accuracy for navigation purposes.
Solution Approach 2:
The patent inverts the approach by using passive acoustic detection and triangulation instead of active imaging and processing. Rather than capturing and analyzing visual images, the system listens for acoustic signatures of obstacles and calculates positions through triangulation, fundamentally simplifying the detection and processing architecture.
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 solution allows UAVs to efficiently navigate to a target while avoiding obstacles without the need for expensive imaging systems, reducing weight and cost, and enabling autonomous operation in various environments, including those where line-of-sight control is not possible.
Implementation Method 1
The sensor array may include a transmitter of electromagnetic signals (e.g., radar and LIDAR) and various receivers for receiving return signals indicating that the transmitted signals are reflected from objects
Implementation Method 2
The sensor array may include a transmitter of electromagnetic signals (e.g., radar and LIDAR) and various receivers for receiving return signals indicating that the transmitted signals are reflected from objects
Implementation Method 3
The object detection system then detects the objects and determines their locations based on the sensor data. For example, the object detection system may triangulate an object's location based on return signals received by multiple sensors
Data Source
Figure 1
Figure 2A~2B
Figure 3A~3B
AI summary
A system for determining a travel path for an autonomous vehicle ("AV") to travel to a target while avoiding objects (i.e., obstacles) without the use of an imaging system is provided. An object sense and avoid ("OSA") system detects objects in an object field that is adjacent to the AV and dynamically generates, as the AV travels, a travel path to the target to avoid the objects. The OSA system repeatedly uses sensors to collect sensor data of any objects in the object field. An object detection system then detects the objects and determines their locations based on triangulating ranges to an object as indicated by different sensors. The path planner system then plans a next travel direction for the AV to avoid the detected objects while seeking to minimize the distance traveled. The OSA system then instructs the AV to travel in the travel direction.