Augmented Manual Flight Control for Obstacle-Aware Speed Constraints
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Solution Overview
Problem
Pilots face challenges in safely navigating aerial vehicles close to obstacles due to the high workload of managing vehicle position while attending to other tasks, making collision prevention hazardous.
Innovation Solution
An augmented manual control mode for aerial vehicles that uses existing sensors to detect obstacles and dynamically sets speed and attitude constraints, adjusting pilot inputs to prevent collisions while allowing free navigation in other directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pilots manually navigate aerial vehicles close to obstacles, then navigation flexibility and task completion capability are improved, but collision risk and pilot workload increase significantly
Solution Approach 1:
The patent introduces an automated control system as an intermediary between the pilot and the aerial vehicle. This system uses sensor data to detect obstacles and automatically adjusts control inputs to maintain safe distances, allowing the pilot to focus on mission tasks while the intermediary system handles collision prevention
Solution Approach 2:
The system continuously monitors sensor data about the environment and vehicle position, processes this information through a world model, and dynamically adjusts control constraints based on detected obstacles. This closed-loop feedback mechanism enables real-time collision prevention while maintaining navigation flexibility
2Productivity
If pilots focus on other tasks during flight, then task efficiency is improved, but control attention and collision monitoring capability deteriorate
Solution Approach 1:
The aerial vehicle's control system performs self-monitoring and self-adjustment regarding obstacle avoidance. The automated system independently processes sensor data, detects obstacles, and modifies control inputs without requiring continuous pilot attention, enabling the pilot to attend to other mission-critical tasks
3Reliability
If automated obstacle avoidance constraints are imposed on pilot inputs, then collision prevention is improved, but navigation freedom and pilot control authority are restricted
Solution Approach 1:
The control constraints are dynamically adjusted based on real-time obstacle detection and vehicle state. The system imposes constraints only when and where needed for collision prevention, while allowing full navigation freedom in directions and areas not threatened by obstacles, thus balancing safety with pilot autonomy
Solution Approach 2:
The automated system applies control constraints locally and selectively only in directions where obstacles are detected, rather than imposing global restrictions. This allows the pilot to maintain full navigation freedom in safe directions while receiving targeted assistance only where collision risk exists
Data Source
AI summary
Systems and methods for controlling an aerial vehicle to avoid obstacles are disclosed. A system can detect, based on a world model generated from sensor data captured by one or more sensors positioned on the aerial vehicle during flight, an obstacle for the aerial vehicle, and trigger an augmented manual control mode responsive to a speed of the aerial vehicle being less than a predetermined threshold and detecting the obstacle. The system can set, responsive to triggering the augmented manual control mode, a speed constraint for the aerial vehicle in a direction of the obstacle based on a distance between the aerial vehicle and the obstacle. The system can receive an instruction to navigate the aerial vehicle in the direction at a second speed, and adjust the instruction to replace the second speed with the speed constraint, causing the aerial vehicle to navigate at the speed constraint.