Drone Flight Route Planning Using 3D Map Alignment
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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, especially in uncharted areas.
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 detection of environmental structures and semantic segmentation for accurate flight route planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a long flight route is calculated in advance for high-speed autonomous flight, then flight speed is improved, but the risk of collision increases when obstacles appear in unobservable areas
Solution Approach 1:
The system performs preliminary actions by calculating a long flight route in advance for high-speed flight, while simultaneously preparing real-time obstacle detection and route recalculation mechanisms to handle unexpected obstacles during flight
Solution Approach 2:
The flight route is made dynamic through real-time obstacle detection and automatic route recalculation. The system transitions from a static pre-calculated route to a dynamic adaptive route that adjusts based on real-time environmental observations, resolving the contradiction between speed and collision risk
2Reliability
If route calculation is performed frequently to avoid obstacles, then collision risk is reduced, but flight speed decreases due to calculation time
Solution Approach 1:
The system implements periodic action by performing full route calculations only when necessary (when obstacles are detected or at key decision points) rather than continuously, while maintaining continuous real-time obstacle monitoring. This reduces calculation overhead while ensuring collision avoidance
3Measurement precision
If three-dimensional real-time observation is performed for accurate environmental recognition, then route accuracy is improved, but processing time increases
Solution Approach 1:
The three-dimensional space is segmented into discrete grid cells creating a three-dimensional occupancy grid map. This segmentation allows the system to process environmental data in manageable units, improving both accuracy in representing the environment and efficiency in processing by focusing computational resources on relevant grid cells rather than the entire space
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.