UAV Path Planning Using Dense Maps for Obstacle Avoidance
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) often lose connection with ground-based controllers, necessitating automatic path determination and navigation to re-establish communication or return to a safe location.
Innovation Solution
UAVs generate dense and sparse maps during flight to create a global graph, using an onboard flight control subsystem for autonomous navigation, allowing them to determine and follow paths that avoid obstacles and return to a launch point or dock based on triggers like battery level or loss of communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automatic path determination and navigation are implemented, then the UAV can autonomously return to a safe location or re-establish communication, but the device complexity increases due to onboard mapping and path planning systems
Solution Approach 1:
The navigation system is divided into distinct functional modules: a mapping module that generates dense and sparse maps, a graph generation module that creates a global graph from these maps, and a path determination module that computes navigation paths. This segmentation allows each module to specialize in specific tasks, improving overall system reliability while managing complexity through modular design.
Solution Approach 2:
The system performs preliminary mapping and graph generation during initial flight operations or when in communication with the ground controller. By pre-computing the global graph and storing it onboard, the UAV prepares navigation data in advance, enabling autonomous path determination later without requiring real-time complex computations when connectivity is lost.
2Measurement precision
If dense maps are generated during flight for accurate path planning, then the path determination precision improves, but the use of energy increases due to continuous mapping operations
Solution Approach 1:
The mapping operation is performed periodically or at specific intervals during flight rather than continuously. The mapping module generates dense maps at selected time points or locations, which are then used to update the global graph. This periodic approach maintains sufficient path planning accuracy while significantly reducing energy consumption compared to continuous mapping.
Solution Approach 2:
The system generates dense maps only for specific regions or at specific times when needed for path planning, rather than continuously mapping the entire environment. The sparse map provides coarse coverage while dense maps are generated selectively in areas requiring detailed navigation, achieving adequate precision with reduced energy expenditure.
Data Source
AI summary
A computer stores dense maps generated by one or more aerial vehicles. The computer generates a global graph based on the dense maps and a sparse map. The computer stores a representation of one or more paths traversed by the one or more aerial vehicles within the global graph. The computer determines a path from an origin location to a destination location based on the global graph. The determined path enables an aerial vehicle to avoid objects.