Drone Fleet Task Replanning After Asset Failure
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Solution Overview
Problem
Conventional unmanned aerial vehicles (UAVs) face issues such as lack of reliability, limited range, and complex coordination of multiple assets, requiring human intervention for operation control.
Innovation Solution
A system for dynamically grouping semi-autonomous drones that includes a communication interface and processors to determine task performance, update plans in response to failures, and autonomously manage asset coordination using leader drones to execute high-level instructions and adapt to environmental changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional drones are remotely piloted and coordinated by human operators, then operational control is maintained, but system complexity and human intervention requirements increase
Solution Approach 1:
The patent segments the coordination function by designating specific drones as 'leader drones' that independently manage task assignment and coordination. This divides the centralized human coordination role into distributed autonomous leader units, reducing the need for human intervention while maintaining operational control through hierarchical segmentation of the drone fleet into leaders and followers.
Solution Approach 2:
The leader drones perform self-service by autonomously determining task assignments, monitoring fleet status, and coordinating operations without continuous human input. The system enables self-organization where drones automatically adapt to failures and reassign tasks, allowing the fleet to manage itself through autonomous decision-making algorithms embedded in the leader drones.
2Productivity
If multiple drones are coordinated through centralized human control, then operational oversight is maintained, but response time and operational efficiency decrease
Solution Approach 1:
Leader drones perform preliminary actions by pre-establishing coordination protocols, pre-assigning tasks based on drone capabilities, and pre-planning response strategies for potential failures. This allows the fleet to operate efficiently without real-time human intervention, as the autonomous leaders have already prepared coordination frameworks and task allocation strategies before operations begin.
Solution Approach 2:
The system implements continuous feedback loops where leader drones monitor the status of all fleet members, receive real-time information about task completion and failures, and dynamically adjust task assignments. This feedback mechanism enables rapid autonomous response to changing conditions, maintaining high operational efficiency without requiring human operators to process each status update.
3Reliability
If conventional drones operate without redundancy, then device simplicity is maintained, but reliability decreases when failures occur
Solution Approach 1:
The patent applies beforehand cushioning by designing the fleet with redundant drones and establishing pre-planned failure response protocols. When a drone fails, the system has pre-prepared replacement strategies where leader drones automatically reassign tasks to remaining operational drones, cushioning the impact of failures without requiring additional human intervention or physical replacement drones during operation.
Data Source
AI summary
A system for asset failure and replacement management is disclosed. The system includes a communication interface and processor(s) configured to: receive an indication that the drone is part of a set of assets, wherein the set of assets are tasked with performing element(s) of task(s), and the set of assets comprises a plurality of drones; determine that at least one drone has experienced a failure; in response to a determination that the at least one drone has experienced the failure, update a plan to an updated plan to perform the task(s); and communicate, via the communication interface, information pertaining to the updated plan, wherein the information pertaining to the updated plan is communicated with at least one remaining drone of the set of assets.