Autonomous Drone Wind Correction for Safe Flight Recovery
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Solution Overview
Problem
Autonomous drones face challenges in navigating and safely returning to a home position or landing due to excessive winds, which can overwhelm their control systems and battery limitations, especially when size and power constraints are considered.
Innovation Solution
The autonomous drone detects excessive winds through sensor data or unanticipated movement, and adjusts its flight plan by returning to a home position or landing in place, prioritizing power allocation to propulsion systems and shutting down non-essential systems to maintain control, with thresholds for nominal and critical wind speeds determining the appropriate action.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous drone continues its original flight plan in excessive wind conditions, then it may complete the intended photography task, but the drone's safety and control are compromised due to overwhelming wind forces
Solution Approach 1:
The drone dynamically adjusts its flight plan based on real-time wind conditions. When excessive wind is detected, the system transitions from executing the original flight plan to implementing a modified plan that prioritizes safety, such as returning to home position or landing at alternative locations. This dynamic adaptation resolves the contradiction by allowing the drone to maintain safety while still completing photographic tasks when conditions permit.
Solution Approach 2:
The system changes operational parameters by comparing current wind speed against nominal and critical thresholds. When wind speed exceeds the critical threshold, the drone changes its operational state from normal flight execution to safety-oriented behavior (return to home or land). This parameter-based decision-making resolves the contradiction by objectively determining when to prioritize safety over task completion.
2Reliability
If the autonomous drone returns to home position or lands in place due to excessive wind, then drone safety is ensured, but the original flight plan and image capture objectives are not completed
Solution Approach 1:
The drone performs partial completion of the flight plan by capturing images at safe locations before returning home or landing. Rather than attempting to complete the entire original flight plan in dangerous conditions, the system captures what it can safely and then aborts, resolving the contradiction by achieving partial objectives while prioritizing safety.
Solution Approach 2:
The drone detects excessive wind conditions in advance and proactively adjusts its flight plan before losing control or crashing. By monitoring wind speed thresholds and preemptively changing behavior, the system ensures safety while minimizing loss of time by not attempting flight in clearly dangerous conditions.
3Reliability
If the autonomous drone allocates more power to propulsion systems to counteract wind, then control and stability are improved, but battery life is reduced due to power constraints
Solution Approach 1:
The system changes power allocation parameters dynamically based on wind conditions. When wind speed exceeds critical thresholds, the drone stops attempting to counteract wind with increased propulsion power and instead executes safety protocols. This resolves the contradiction by avoiding excessive energy consumption that would deplete the battery while maintaining control stability through intelligent decision-making rather than brute-force propulsion.
Solution Approach 2:
The drone dynamically adjusts power distribution to propulsion systems based on real-time wind assessment. Rather than continuously allocating maximum power to counteract wind, the system adaptively increases power only when necessary and safe to do so, resolving the contradiction between maintaining control stability and managing battery consumption efficiently.
4Measurement precision
If the autonomous drone increases sensor and processing capabilities to detect and respond to wind conditions, then navigation accuracy is improved, but device size and complexity increase
Solution Approach 1:
The system uses an intermediary approach by leveraging existing navigation sensors (GPS, inertial measurement units) and processing wind information through software algorithms rather than adding complex dedicated wind sensors. This resolves the contradiction by achieving sufficient wind detection accuracy using existing system components, avoiding increased device complexity.
Solution Approach 2:
The drone's existing navigation and control sensors serve multiple functions: primary navigation, position tracking, and wind condition detection. By making these existing sensors multi-functional, the system achieves wind detection accuracy without adding dedicated sensors, thus resolving the contradiction between measurement precision and device complexity.
Data Source
AI summary
Systems, computer readable medium and methods for navigation correction for excessive wind in an autonomous drone are disclosed. Excessive winds can be a particular problem for small autonomous drones as safety and retrieval of the autonomous drones is important and the autonomous drones often have limited thrust and batteries. Autonomous drones are disclosed that detect and correct flight plans when excessive winds are detected. The autonomous drone determines based on the severity of the excessive winds whether to return to a home position which is typically a position of a user of the autonomous drone or to land in place. If the excessive winds subside, then the autonomous drone returns to its original flight plan at the point where the autonomous drone was blown off course by the excessive winds. The autonomous drone detects excessive winds either directly by sensor data or inferentially by unanticipated movement of the autonomous drone.