UAV Depth Imaging Collision Avoidance in GPS-Denied Flight
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Solution Overview
Problem
Current unmanned aerial vehicles (UAVs) face challenges in obstacle avoidance, particularly in GPS-denied environments where traditional navigation systems fail, leading to potential collisions due to reliance on GPS for positioning and lack of detailed obstacle detection.
Innovation Solution
The implementation of a collision avoidance system using depth sensors to generate a spherical map of the UAV's vicinity, determining obstacles and their movement information, and calculating a virtual force vector to control the UAV's flight path and avoid collisions without the need for GPS data, utilizing depth imaging sensors and processors to convert depth camera data into accessible data structures for real-time obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional GPS-based navigation systems are used for UAV flight control, then the UAV can maintain accurate positioning and follow predefined flight paths, but the UAV cannot operate reliably in GPS-denied environments and is vulnerable to collisions when GPS signals are unavailable
Solution Approach 1:
The patent introduces depth sensors as an intermediary system between the UAV and its environment, enabling the UAV to perceive obstacles and navigate autonomously without GPS. The depth sensors provide real-time spatial information that mediates the navigation decision-making process, allowing the UAV to operate independently in GPS-denied environments while maintaining collision avoidance capability
Solution Approach 2:
The patent replaces the GPS-based mechanical navigation system with a sensor-based perception and avoidance system. Instead of relying on satellite signals for positioning, the UAV uses depth sensors to detect obstacles and dynamically adjust its flight path, substituting passive GPS navigation with active sensor-driven obstacle avoidance
2Reliability
If additional sensors are added to enhance obstacle detection capability, then the UAV can achieve better collision avoidance performance, but the device complexity and cost increase
Solution Approach 1:
The patent makes the depth imaging system multi-functional by using it for both obstacle detection and environmental mapping. The same depth sensor that detects obstacles also generates spherical maps for navigation, eliminating the need for separate sensors and reducing overall system complexity while maintaining high collision avoidance accuracy
Solution Approach 2:
The patent combines obstacle detection and environmental perception functions into a single depth imaging system. By merging these functions, the system achieves comprehensive obstacle avoidance capability without the complexity of multiple separate sensor systems, reducing both hardware complexity and processing overhead
Data Source
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AI summary
According to various aspects, a collision avoidance method may include: receiving depth information of one or more depth imaging sensors of an unmanned aerial vehicle; determining from the depth information a first obstacle located within a first distance range and movement information associated with the first obstacle; determining from the depth information a second obstacle located within a second distance range and movement information associated with the second obstacle, the second distance range is distinct from the first distance range, determining a virtual force vector based on the determined movement information, and controlling flight of the unmanned aerial vehicle based on the virtual force vector to avoid a collision of the unmanned aerial vehicle with the first obstacle and the second obstacle.