Methods and systems for assigning tasks to a constellation of satellites
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Solution Overview
Problem
As the number of satellites in a fleet increases, managing and scheduling tasks across the fleet becomes impractical for human operators due to varying satellite orbits, acquisition constraints, and task-specific requirements, leading to inefficiencies and delays in task allocation.
Innovation Solution
A method and system using computer processors to assign tasks to satellites by generating scheduling scores based on task constraints, including priority, satellite availability, and downlink opportunities, optimizing task allocation across a constellation of satellites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the fleet of satellites is expanded to increase coverage and task execution capability, then productivity and task completion speed are improved, but device complexity and scheduling difficulty increase significantly
Solution Approach 1:
The scheduling system performs self-service by automatically generating task assignments and scheduling decisions without requiring human intervention. The system evaluates multiple satellites, constraints, and opportunities autonomously to produce optimized schedules, resolving the contradiction by making the complex scheduling process self-managing rather than human-managed
Solution Approach 2:
The patent replaces the mechanical human-operated scheduling process with an automated computational system. Instead of human operators manually assigning tasks to satellites, the system uses computer processors to automatically evaluate constraints, generate schedules, and assign tasks, thereby handling the increased complexity that comes with fleet expansion
2Productivity
If automated scheduling algorithms are implemented to improve efficiency, then productivity increases, but ease of operation decreases due to system complexity
Solution Approach 1:
The patent extracts the complex scheduling decision-making process from human operators and places it into the automated system. The system takes out the burden of evaluating constraints, calculating opportunities, and making assignments, leaving operators with simpler oversight and control functions while maintaining high scheduling efficiency
3Manufacturing precision
If multiple constraints are considered for each task assignment to improve accuracy, then manufacturing precision of task allocation increases, but device complexity increases
Solution Approach 1:
The patent segments the scheduling process into distinct computational steps: identifying constraints, evaluating opportunities, calculating scores, and making assignments. This segmentation allows the system to handle multiple constraints systematically without becoming unmanageably complex, as each constraint type is processed in a structured sequence
Data Source
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AI summary
One or more computer processors receive one or more tasks. Each task is associated with a task priority. For each task, a list of one or more opportunities is generated. Each opportunity corresponds to a satellite from the constellation of satellites potentially performing the task. Each opportunity is associated with an expected time for the satellite to potentially perform the task. Each opportunity is ranked based on each task priority and based on each expected time. One or more opportunities are selected based on the ranking. For each selected opportunity, the task associated with the selected opportunity is assigned to the satellite associated with the selected opportunity.