3D Observation Alignment for Long-Range Autonomous Drone Routing
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Solution Overview
Problem
Existing autonomous flight systems, such as drones, face challenges in calculating accurate and efficient flight routes due to the need for time-consuming route calculations and the risk of collisions from unobservable obstacles.
Innovation Solution
An information processing apparatus and method that generates a three-dimensional real-time observation result using self-position estimation and distance measurement information, aligns it with a prior map, and expands the result to include unobserved areas, enabling the calculation of a long flight route for high-speed autonomous flight.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a long flight route is calculated in advance to enable high-speed autonomous flight, then flight speed is improved, but the risk of collision increases due to unobservable obstacles in not-yet-observation areas
Solution Approach 1:
The system performs preliminary actions by acquiring a prior map of the not-yet-observation area before the flight object actually reaches that area. This prior map is obtained through alignment and expansion of real-time observation results, allowing the flight route to be calculated in advance with knowledge of potential obstacles, thus enabling both high-speed flight and collision avoidance
Solution Approach 2:
A prior map serves as an intermediary between real-time observation and future flight planning. The prior map is created by aligning and expanding current observation data, acting as a mediator that provides predictive information about unobserved areas, enabling safe long-range route calculation without direct real-time observation
2Reliability
If real-time observation is used alone for route calculation, then collision avoidance is improved, but flight speed decreases due to inability to plan long routes
Solution Approach 1:
The system merges real-time observation results with prior map information to create a comprehensive view for route calculation. By combining current sensor data with expanded predictions of unobserved areas, the system achieves both accurate collision avoidance and the ability to plan long-range high-speed routes
3Measurement precision
If the three-dimensional real-time observation result is expanded using prior map information, then the accuracy of unobserved area prediction is improved, but the computational complexity increases
Solution Approach 1:
The expansion process is segmented into distinct steps: first aligning the real-time observation result with the prior map coordinate systems, then performing the expansion operation. This segmentation allows the complex task to be broken into manageable computational stages, improving prediction accuracy while controlling computational complexity through systematic processing
Data Source
AI summary
To enable high-speed autonomous flight of a flight object. A three-dimensional real-time observation result is generated on the basis of self-position estimation information and three-dimensional distance measurement information. A prior map corresponding to a three-dimensional real-time observation result is acquired. The three-dimensional real-time observation result and the prior map are aligned. After the alignment, the three-dimensional real-time observation result is expanded on the basis of the prior map. A flight route is set on the basis of the three-dimensional real-time observation result having been expanded. In the flight object such as a drone, a somewhat long flight route can be accurately calculated at a time in a global behavior plan, which enables high-speed autonomous flight of the flight object.