Autonomous Drone Flight Path Calculation System
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Solution Overview
Problem
Conventional methods for controlling drone flight paths require constant human intervention to correct for wind effects, especially in urban areas, where smaller drones are more susceptible to wind and prone to collisions if not corrected swiftly.
Innovation Solution
A flight path calculation system and method that uses three-dimensional map data, wind condition data, and Doppler lidar technology to autonomously recalculate and adjust drone flight paths, avoiding dangerous wind areas and enabling emergency landings when necessary, without human control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a drone is operated with constant human intervention to correct trajectory, then flight safety is improved, but operator burden increases
Solution Approach 1:
The drone is equipped with autonomous flight control functionality that automatically adjusts its trajectory based on wind condition data without requiring constant human intervention. The system self-corrects by comparing actual position with planned path and autonomously modifying flight parameters, thereby maintaining flight safety while eliminating operator burden.
Solution Approach 2:
The system continuously acquires wind condition data during flight and uses this feedback to automatically adjust the drone's flight path. The control system processes real-time wind information and dynamically modifies trajectory calculations, creating a closed-loop control system that maintains safety without human intervention.
2Device complexity
If a small drone is used to reduce cost and size, then device complexity is reduced, but susceptibility to wind increases
Solution Approach 1:
The system performs preliminary acquisition of wind condition data before the drone enters windy areas by continuously monitoring wind conditions along the planned flight path. This advance information allows the autonomous control system to pre-calculate trajectory adjustments and proactively compensate for upcoming wind effects, enabling small drones to operate safely despite their high wind susceptibility.
Solution Approach 2:
The flight control system dynamically adjusts flight parameters in real-time based on acquired wind condition data. The system continuously modifies trajectory, speed, and altitude to adapt to changing wind conditions, allowing small drones to maintain stable flight by constantly optimizing their flight path rather than using fixed control parameters.
3Ease of operation
If autonomous flight control is implemented to reduce operator burden, then ease of operation is improved, but ability to handle complex wind conditions worsens
Solution Approach 1:
The system introduces a dedicated autonomous flight control system that acts as an intermediary between the drone's flight control and the external environment. This intermediate control layer processes complex wind condition data and translates it into appropriate flight adjustments, shielding the simplicity of autonomous operation from the complexity of wind handling while maintaining reliability through sophisticated algorithms.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system allows drones to fly autonomously, reducing the burden on operators and minimizing collisions by predicting and adapting to wind conditions, ensuring safe and efficient navigation through complex environments.
Implementation Method 1
Coherent Doppler Lidar (CDL) has been suggested, in which wind velocities and/or aerosol amount are acquired by irradiating a laser light into atmosphere and acquiring scattering from atmospheric dust (aerosol) with a telescope
Implementation Method 2
acquiring scattering from atmospheric dust (aerosol) with a telescope
Data Source
AI summary
In an uninhabited aircraft flight management system 1, there is a three-dimensional map data storage section 172 for storing three-dimensional map data in horizontal and height directions where no ground objects exist and where an uninhabited aircraft 6 is allowed to fly, a current position acquisition section 175 for acquiring a current position, a transport instruction acquisition section 166 for acquiring a destination, a path calculation section 167 for calculating a path, a lidar data acquisition section 121 for acquiring wind condition data, a dangerous wind condition area judgement section 123 for calculating a warning area where flight should be avoided, from the wind condition data, and a path recalculation section 164 for recalculating the path avoiding the warning area when the path calculated by the path calculation section 167 is one which passes through the warning area calculated by section 123.