UAV Flight Control System for Intuitive Tap-and-Go Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current flight navigation systems for aerial vehicles are hindered by the lack of an easy-to-use interactive control and guidance system, requiring operators with aviation experience and offering limited real-time automatic control capabilities, which reduces their effectiveness in various applications, especially in environments with poor GPS signal reception or obstacles.
Innovation Solution
The development of improved flight control systems that allow intuitive operation through a human-system interface, enabling automatic detection of obstacles and adjustment of motion paths to avoid collisions, using 'tap-and-go' functions and motion path optimization based on object characteristics and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual control is used to operate the aerial vehicle, then the operator can directly control the vehicle to fly in desired directions and avoid obstacles, but the operator requires aviation experience and manual skill, increasing the complexity of operation
Solution Approach 1:
The system enables the aerial vehicle to autonomously navigate and avoid obstacles without requiring continuous manual input from the operator. The vehicle performs self-service functions including automatic path planning, obstacle detection, and collision avoidance, thereby simplifying operation while managing complexity through automated decision-making algorithms
Solution Approach 2:
An automated control system acts as an intermediary between the operator's high-level commands and the vehicle's low-level flight control. This intermediary layer translates simple user inputs into complex coordinated actions, reducing the skill requirement while maintaining effective control through hierarchical command structures
2Productivity
If automated control is implemented to reduce manual piloting burden, then users can focus on payload operations, but the system requires advanced algorithms for path planning and obstacle detection in diverse environments
Solution Approach 1:
The automated control system is divided into modular functional components including path planning module, obstacle detection module, and motion execution module. Each module handles specific tasks independently, allowing the system to achieve high productivity through coordinated operation of specialized subsystems while managing overall complexity through functional decomposition
Solution Approach 2:
The control system is designed to perform multiple functions including navigation, obstacle avoidance, and adaptive path replanning using a unified set of algorithms. This multi-functionality enables the system to handle diverse operational scenarios and environmental conditions with a single integrated platform, increasing productivity without proportionally increasing complexity
3Adaptability or versatility
If the aerial vehicle operates in environments with poor GPS signal reception or obstacles, then it can serve more diverse applications, but the reliability of navigation and obstacle avoidance is compromised
Solution Approach 1:
The system continuously monitors environmental conditions including GPS signal quality and obstacle proximity, using sensor feedback to dynamically adjust navigation strategies. When GPS signals are poor, the system switches to alternative navigation methods based on visual odometry and terrain mapping, maintaining reliability across diverse environments through adaptive feedback control
Solution Approach 2:
The system performs preliminary environmental assessment and pre-plans multiple alternative paths before execution. By anticipating potential obstacles and signal degradation zones in advance, the vehicle prepares contingency navigation strategies that ensure reliable operation in diverse and challenging environments without compromising safety
Data Source
AI summary
A method for determining a target direction for a movable object includes providing an image on a computer-implemented display, obtaining a position of a selected point on the image in response to a user selecting the point on the image, and determining the target direction based on the position of the selected point on the image.