Drone Navigation Using Spatial Obstruction Maps in Remote Areas
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Solution Overview
Problem
Navigation of drones in complex and underserved environments, particularly in areas with limited data communication, is difficult and unreliable, especially for autonomous or semi-autonomous drones.
Innovation Solution
A spatial obstruction database representing physical features and airspace restrictions is used to generate navigation paths, utilizing techniques like RRT* exploration and R-tree data structures to optimize computational resources and determine cost-effective paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional navigation systems are used in complex environments, then navigation reliability is improved, but device complexity and computational resource requirements increase
Solution Approach 1:
The navigation system segments the complex environment into discrete spatial obstructions and navigable spaces. The configuration space is divided into cells that can be independently evaluated, allowing the system to manage complexity by breaking down the continuous navigation problem into discrete, manageable units.
Solution Approach 2:
A configuration space representation serves as an intermediary between the physical environment and the navigation algorithm. This abstract representation mediates the complex spatial relationships, transforming them into a format that can be efficiently processed by pathfinding algorithms while maintaining navigation reliability.
2Extent of automation
If autonomous navigation is implemented in remote environments, then operational autonomy is improved, but computational resource consumption increases
Solution Approach 1:
The system performs preliminary actions by pre-computing the configuration space and identifying spatial obstructions before actual navigation begins. This advance preparation allows the autonomous drone to execute navigation with minimal real-time computational overhead, reducing energy consumption during operation while maintaining high autonomy.
Solution Approach 2:
The navigation system computes only the necessary portion of the configuration space required for the current navigation task rather than the entire environment. This partial computation approach reduces energy consumption while still providing sufficient information for autonomous operation in remote areas.
3Reliability
If detailed spatial analysis is performed to avoid obstructions, then navigation safety is improved, but processing time increases
Solution Approach 1:
The system replaces complex mechanical spatial analysis with an efficient data structure-based approach. The configuration space is represented using optimized data structures that allow rapid querying of obstruction information, maintaining navigation safety while significantly reducing processing time compared to traditional geometric analysis methods.
Data Source
AI summary
Systems and methods are described herein that facilitate the navigation of drones, including autonomous and semi-autonomous drones. These systems and methods particularly applicable to the facilitation of drones in underserved environments. For example, the systems and methods can facilitate the navigation of drones using a spatial obstruction database. In these embodiments the spatial obstruction database can abstract obstructions in a variety of ways, including as defined subregions. As other examples, the systems and methods can facilitate the navigation of drones using techniques for determining navigation paths. As other examples, the systems and methods can facilitate the navigation of drones using techniques for evaluating navigation paths to determine if line-of-sight path segments are open for navigation. As will be described below, these systems and methods are particularly applicable to the navigation of autonomous and semi-autonomous drones that may have limited processing and memory capabilities.