Drone Docking Control Using Environmental Feedback on Moving Vehicles
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Solution Overview
Problem
Current drone technology struggles to accurately and stably dock on a moving vehicle, especially in unfavorable environmental conditions such as poor road conditions or windy conditions, as it relies solely on drone self-information without considering external environmental data.
Innovation Solution
A system and method where a moving platform on a vehicle collects and processes current and historical environmental data to generate recommended flight parameters for the drone, adjusting its flight parameters for stable docking, including instructions to avoid docking during adverse conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the drone docks based solely on its own information without environmental data, then the system complexity is low, but the docking precision and stability deteriorate in unfavorable environmental conditions
Solution Approach 1:
The patent introduces environmental data as an intermediary element that mediates between the drone's self-information and the docking decision. The environmental data (weather conditions, road conditions, location information) acts as a mediator that helps the drone assess whether current conditions are suitable for docking, thereby improving docking precision without requiring direct complex interactions between drone and environment
Solution Approach 2:
The patent implements feedback by continuously monitoring environmental data and using it to adjust docking decisions. The system collects environmental information, compares it against predefined thresholds or historical data, and provides feedback to the docking control system to either proceed with or postpone docking, creating a closed-loop control system that improves precision
2Reliability
If the drone attempts to dock during adverse environmental conditions, then the productivity is maintained, but the reliability of docking deteriorates
Solution Approach 1:
The patent applies preliminary anti-action by proactively identifying adverse environmental conditions before docking attempts are made. The system pre-assesses environmental factors (wind speed, rain, road conditions) and prevents docking attempts when conditions are unfavorable, thereby avoiding unreliable docking while maintaining overall system productivity by only attempting docking when conditions are suitable
Solution Approach 2:
The system performs preliminary action by collecting and analyzing environmental data before the actual docking process. This preliminary assessment of environmental conditions allows the drone to make informed decisions about whether to proceed with docking, ensuring reliability is maintained without unnecessarily delaying productive operations
3Reliability
If the drone waits for optimal environmental conditions to dock, then the docking stability improves, but the time required for docking increases
Solution Approach 1:
The patent applies partial action by monitoring only the most critical environmental parameters that significantly impact docking stability. Rather than waiting for all environmental conditions to be perfectly optimal, the system focuses on key factors (such as wind speed thresholds or severe weather conditions) and proceeds with docking when these critical parameters are acceptable, reducing time loss while maintaining adequate stability
Data Source
AI summary
A system and a method for drone docking are provided. The method includes: setting a moving platform on a vehicle; obtaining, by the moving platform, current environmental data and historical environmental data corresponding to the moving platform; generating, by the moving platform, a recommended flight parameter according to the current environmental data and the historical environmental data, and transmitting the recommended flight parameter to a drone; and adjusting, by the drone, a flight parameter of the drone according to the recommended flight parameter to dock on the moving platform.


