Dynamic Drone Asset Grouping for Adaptive Task Coordination
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Solution Overview
Problem
Conventional unmanned aerial vehicles (UAVs) face issues such as reliability, speed, range limitations, and complex coordination of multiple assets, which hinder efficient task performance and operation management.
Innovation Solution
A system and method for grouping semi-autonomous drones that dynamically determine and adjust asset sets based on task capabilities and characteristics, enabling decentralized coordination and adaptive task planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional drones are remotely piloted, then ease of operation is maintained, but reliability and performance are adversely affected
Solution Approach 1:
The drone system performs self-coordination and self-management through automated asset grouping algorithms and inter-drone communication protocols, eliminating the need for continuous human intervention while maintaining operational reliability
Solution Approach 2:
The patent accelerates the transition from manual control to autonomous operation by implementing sophisticated automated coordination systems that rapidly manage multiple drones without human operators
2Productivity
If multiple assets are coordinated by a user in a control center, then ease of operation is maintained, but device complexity and coordination difficulty increase
Solution Approach 1:
The coordination function is segmented and distributed to individual drones through autonomous asset grouping, where each drone independently determines its role and coordinates with others through standardized communication protocols, eliminating the need for centralized control complexity
Solution Approach 2:
The patent introduces an automated asset grouping system as an intermediary layer that manages coordination between drones through algorithmic decision-making and standardized communication interfaces, reducing overall system complexity
3Adaptability or versatility
If fixed asset groups are used for operations, then ease of operation is maintained, but adaptability to environmental changes and fault tolerance decrease
Solution Approach 1:
The asset grouping system dynamically reconfigures drone assignments based on real-time environmental conditions, asset availability, and task requirements through automated algorithms that continuously evaluate and adjust group compositions without human intervention
Solution Approach 2:
The system changes operational parameters by automatically adjusting asset group configurations in response to varying task requirements and environmental conditions, enabling flexible adaptation while maintaining manageable complexity through standardized protocols
Data Source
AI summary
A system and method for grouping assets is disclosed. The system includes one or more processors configured to: receive, via the communication interface, data associated with one or more tasks to be performed by a set of assets, determine, from among a plurality of assets, the set of assets to perform the one or more tasks, including determining one or more capabilities associated with one or more characteristics of the one or more tasks, and determining the plurality of drones based at least in part on the one or more capabilities associated with one or more characteristics of the one or more tasks, and one or more drone capabilities respectively associated with the drones, and communicate an instruction to at least one drone in the set of assets, the instruction indicating that the one or more tasks are to be completed by the at least one drone.