Multi-Drone Mission Configurator for Adaptive Emergency Response
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Solution Overview
Problem
Current drone systems for emergency response missions are limited by manual operation and lack of autonomy, which restricts their effectiveness in diverse scenarios such as search-and-rescue, surveillance, and delivery, as they often require human intervention and cannot adapt quickly to changing situations.
Innovation Solution
A system that configures and manages multiple autonomous drones with varying levels of autonomy, allowing them to collaborate and adapt through semi-autonomous operation, using a software product line approach that enables mission-specific configurations and dynamic task management, including autonomy level adjustments during missions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual operation is used for drone control, then human operators can make decisions, but response time is slow and human intervention is required continuously
Solution Approach 1:
The patent segments the drone control system into multiple autonomous modules (navigation, task execution, collision avoidance, communication) that can operate independently. This segmentation enables high-level autonomy while keeping the overall system manageable through modular design, resolving the contradiction between automation extent and device complexity.
Solution Approach 2:
The system performs preliminary actions by pre-programming multiple autonomy levels and mission-specific configurations that are ready to execute without human intervention. The drones are pre-equipped with decision-making algorithms and task libraries, allowing them to autonomously respond to situations, thereby increasing automation while the pre-configured nature keeps complexity controlled.
2Adaptability or versatility
If single drone operation is used, then control is simple, but mission effectiveness in diverse scenarios is limited
Solution Approach 1:
The patent implements universality by designing drones with multi-functional capabilities and a standardized control system that can execute various mission types (search-and-rescue, surveillance, delivery, mapping) using the same hardware platform. The configurator system allows single drones to be adapted for different missions through software configuration, achieving high mission adaptability without increasing physical device complexity.
Solution Approach 2:
The system employs dynamics by allowing real-time adjustment of autonomy levels and mission parameters during operation. The configurator enables dynamic reconfiguration of drone behavior and task priorities based on changing mission requirements, providing operational versatility while maintaining manageable complexity through software-based adaptability rather than hardware changes.
3Productivity
If high autonomy level is implemented, then response time improves and human intervention is reduced, but system complexity increases
Solution Approach 1:
The control system is segmented into distinct autonomy modules (navigation, task execution, obstacle avoidance, communication) that can be independently developed and tested. This modular segmentation enables rapid implementation of high-level autonomy features without overwhelming system complexity, as each module can be optimized separately and integrated through standardized interfaces.
Solution Approach 2:
The patent uses copying by implementing standardized autonomy level profiles and mission templates that can be replicated across multiple drones. Instead of programming each drone individually with complex autonomy logic, pre-configured autonomy profiles are copied and adapted, significantly reducing the complexity burden while maintaining high response times across the entire fleet.
Data Source
AI summary
A method for configuring a multiple autonomous drone mission includes displaying, a plurality of queries on a display of the computing device. The method further includes receiving, via a user interface, a plurality of inputs responsive to the plurality of queries. At least a first input of the plurality of inputs specifies a type of mission to be performed and at least a second input of the plurality of inputs specifies a geographical area in which a mission to be performed will be carried out. The method further includes automatically determining, based on the plurality of inputs, an initial location to move to for each of a plurality of drones available for implementing the mission. The method further includes automatically determining, based on the plurality of inputs, a series of tasks for each of the plurality of drones.