Autonomous Flight Planning Using 3D Spatial Models
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Solution Overview
Problem
Current flight planning systems for autonomous aerial vehicles require an initial flyover to create a detailed survey plan, which is inefficient and resource-intensive, especially for complex environments, and often necessitates manual interventions and iterative modifications.
Innovation Solution
The system generates flight plans using 3D spatial models and precision obstacle databases, allowing for remote planning that computes absolute or relative position values to survey static or movable targets without an initial flyover, enhancing dispatcher productivity and operational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an initial flyover is conducted to create a detailed survey plan, then the flight plan can be based on actual imaging data of the survey target, but it requires additional time and resources for the preliminary flyover
Solution Approach 1:
The system performs preliminary actions by retrieving pre-existing 3D spatial models, terrain data, and obstacle information from databases before flight plan generation. This eliminates the need for a preliminary flyover while still enabling accurate flight planning based on comprehensive spatial information about the survey target and environment.
Solution Approach 2:
The system uses copied data from external sources (3D spatial models from databases, terrain models, obstacle databases) instead of creating new data through preliminary flights. These copied spatial representations are sufficient for generating accurate flight plans without requiring physical reconnaissance flights.
2Adaptability or versatility
If manual interventions and iterative modifications are used to design flight plans, then the flight plan can be adjusted to meet specific mission requirements, but it increases device complexity and reduces productivity
Solution Approach 1:
The system performs self-service by automatically generating flight plans using the received spatial model and mission parameters. The processor autonomously computes the flight plan without requiring manual intervention or iterative modifications by dispatchers, thereby maintaining adaptability while significantly improving productivity.
Solution Approach 2:
The system enables flight plan customization through parameter changes by accepting mission-specific parameters (such as survey altitude, speed, imaging parameters) and automatically adjusting the flight plan accordingly. This maintains versatility while eliminating manual complexity.
3Device complexity
If a two-dimensional navigation map is used for flyover planning, then the system can operate with simpler data requirements, but it cannot provide complete survey coverage of three-dimensional structures
Solution Approach 1:
The system transitions from two-dimensional navigation maps to three-dimensional spatial models for flight plan generation. By using 3D spatial information about the survey target and environment, the system achieves complete survey coverage of three-dimensional structures while the processor handles the complexity of 3D path planning automatically.
Data Source
AI summary
The present disclosure provides systems and methods for flight planning for an autonomous aerial vehicle. The systems and methods perform a processor executed process of receiving a request for flight planning and retrieving a model for the structure or the feature of interest from one or more databases. The request identifies a structure or a feature of interest to be surveyed by the autonomous aerial vehicle. The one or more databases include a database including models of terrain, airports and obstacles or a database including models of manufactured articles based on original equipment manufacturer (OEM) specifications or computer aided design (CAD) models. The process includes computing a flight plan that completely surveys the structure or completely surveys the feature of interest based on the retrieved model. The flight plan defines a search pattern with position values. The process includes uplinking the flight plan to the autonomous aerial vehicle.