AR Route Planning for Drone Collision Avoidance
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Solution Overview
Problem
Conventional systems for generating pre-planned flight paths for drones are limited by outdated maps and fail to account for current obstacles, leading to potential collisions and mismatched user intentions.
Innovation Solution
An augmented reality (AR) experience is used to visualize the environment in real-time, allowing users to input and adjust flight paths by tracing desired routes, which are then converted into autonomous travel instructions for drones, incorporating real-time environmental data and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems use outdated maps for flight path planning, then the system complexity is reduced, but the reliability of collision avoidance deteriorates
Solution Approach 1:
The system performs preliminary scanning of the environment using cameras and sensors before generating the flight path. This pre-scanning creates an up-to-date collision model that is then used for route calculation, ensuring reliability without requiring complex real-time processing during flight.
Solution Approach 2:
The patent introduces an intermediary collision model that translates real-time environmental data into a format usable for flight path planning. This model acts as a mediator between the physical environment and the flight control system, improving reliability without directly increasing system complexity.
2Reliability
If real-time environmental scanning is performed to identify current obstacles, then the reliability of flight safety is improved, but the loss of time for flight planning increases
Solution Approach 1:
The system performs environmental scanning and collision model generation as preliminary actions before the user inputs the flight route. By completing these time-consuming tasks in advance, the system ensures flight safety without delaying the actual flight planning process.
Solution Approach 2:
The system performs scanning in the general area of interest before the user finalizes their route. This partial scanning approach provides sufficient safety information without requiring exhaustive scanning of every possible area, thus balancing safety with time efficiency.
3Adaptability or versatility
If users manually trace flight routes in AR environment, then the adaptability to user intentions is improved, but the ease of operation deteriorates due to complex interaction
Solution Approach 1:
The system creates a virtual copy of the real-world environment in the AR interface, complete with detected obstacles and terrain features. Users interact with this simplified copy rather than raw sensor data, making route tracing intuitive while maintaining adaptability to user intentions.
Solution Approach 2:
The AR interface serves multiple functions simultaneously: it displays the real-world view, overlays detected obstacles, shows the planned route, and provides interaction controls. This multi-functionality consolidates complex operations into a single unified interface, improving ease of operation while maintaining adaptability.
4Manufacturing precision
If detailed collision models are generated from pre-scanning, then the manufacturing precision of flight path planning is improved, but the loss of time for data processing increases
Solution Approach 1:
The collision model generation is performed as a preliminary action before the user traces the flight route. This allows detailed processing to occur in advance, ensuring high precision in the final flight path without delaying user interaction or route planning.
Solution Approach 2:
The system generates collision models with sufficient detail for the specific area of interest rather than creating exhaustive models of the entire environment. This partial modeling approach provides the necessary precision for safe flight planning while reducing overall data processing time.
Data Source
AI summary
An apparatus such as a head-mounted display (HMD) may have a camera for capturing a visual scene for presentation via the HMD. A user of the apparatus may specify a pre-planned travel route for a vehicle within the visual scene via an augmented reality (AR) experience generated by the HMD. The pre-planned travel route may be overlaid on the visual scene in the AR experience so that the user can account for real-time environmental conditions determined through the AR experience. The pre-planned travel route may be transferred to the vehicle and used as autonomous travel instructions.