Non-Imaging Obstacle Sensing for Autonomous Vehicle Path Planning
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Solution Overview
Problem
Current navigation systems for unmanned aerial vehicles (UAVs) that rely on image processing to detect obstacles are expensive and heavy, making them impractical for commercial and recreational use due to the need for high-end processing systems and significant computational and storage resources.
Innovation Solution
The Object Sense and Avoid (OSA) system uses a sensor array to detect objects without imaging, triangulating their locations and dynamically planning a travel path to avoid obstacles, minimizing distance traveled while maintaining clearance, using a path planner system and data structures to determine suitable travel directions based on transit volumes and clearance criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image processing navigation systems are used to detect obstacles, then obstacle detection capability is improved, but system cost and weight increase significantly
Solution Approach 1:
The patent extracts only the essential obstacle detection function from complex image processing systems. Instead of using full imaging systems with cameras and image processors, the invention uses simplified sensor arrays (acoustic, electromagnetic, or other non-imaging sensors) that detect obstacles through physical field interactions, eliminating the need for heavy imaging hardware while maintaining detection capability.
Solution Approach 2:
The patent replaces mechanical/optical imaging systems with field-based detection systems. Instead of using cameras that capture light reflections, the invention employs acoustic sensors, electromagnetic sensors, or other non-optical fields to detect obstacles, substituting complex optical-mechanical systems with simpler field interaction-based detection.
2Reliability
If image processing navigation systems are used to detect obstacles, then obstacle detection capability is improved, but system cost increases due to computational resources
Solution Approach 1:
The patent extracts only the essential detection data from the environment, ignoring complex visual information processing. The sensor arrays collect minimal necessary data about obstacle presence and position through field interactions, eliminating the need for heavy computational image processing, storage, and analysis infrastructure.
Solution Approach 2:
The patent uses simple, inexpensive sensor arrays that can be easily manufactured and replaced if needed, rather than expensive, complex image processing systems. The sensor hardware is basic and the processing requirements are minimal, making the overall system much more cost-effective for commercial and recreational UAV applications.
3Device complexity
If remote control with line of sight is used, then system cost is reduced, but operational flexibility and safety are limited
Solution Approach 1:
The patent enables the UAV to autonomously detect and respond to obstacles using onboard sensor arrays and automated path planning algorithms. The system performs obstacle detection and navigation decisions independently without requiring continuous operator intervention or line-of-sight visual contact, allowing the UAV to operate flexibly beyond visual range while maintaining safety.
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
Enables efficient and lightweight obstacle avoidance for UAVs without the need for expensive imaging systems, allowing for real-time path planning and collision avoidance, applicable to various autonomous vehicles and robotic systems, improving safety and operational efficiency.
Implementation Method 1
The sensor array may transmit radar signals and receive the return signals that are reflected by the objects.
Implementation Method 2
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
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.