Autonomous Machine Scheduling for Adaptive Task Allocation
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Solution Overview
Problem
Existing autonomous grounds maintenance machines lack an efficient method to determine and adapt their operating schedules to changing conditions without requiring extensive user input, leading to suboptimal maintenance of work regions.
Innovation Solution
The implementation of a scheduling system that determines windows of availability and assigns operational tasks based on total operation time, allowing for adaptive scheduling and user input modifications, while prioritizing tasks and adjusting to environmental and containment zone-specific needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous machines operate without scheduling optimization, then they can perform tasks continuously, but maintenance quality deteriorates due to lack of adaptation to changing conditions
Solution Approach 1:
The operating schedule is made dynamic by continuously monitoring operational data and automatically adjusting task timing and allocation based on changing work region conditions, machine status, and environmental factors, rather than following fixed predetermined schedules
Solution Approach 2:
The autonomous machine performs self-scheduling by automatically determining optimal operating times and task allocation based on its own operational data and sensor inputs, reducing the need for external user intervention while maintaining reliable maintenance quality
2Productivity
If extensive user input is required for scheduling, then task allocation can be optimized, but user burden increases significantly
Solution Approach 1:
The system automatically generates and adjusts operating schedules by processing operational data from sensors and work region monitors, enabling intelligent task allocation without requiring users to manually input scheduling preferences or constraints
Solution Approach 2:
The scheduling system continuously receives feedback from operational data and work region conditions, automatically refining task allocation decisions to maintain high productivity while eliminating the need for ongoing user input and adjustment
3Adaptability or versatility
If fixed operating schedules are used, then scheduling simplicity is maintained, but adaptability to changing conditions deteriorates
Solution Approach 1:
The operating schedule transitions from a static fixed plan to a dynamic adaptive system that automatically adjusts task timing and allocation in response to real-time changes in work region conditions, machine status, and environmental factors
Solution Approach 2:
The system performs preliminary analysis of operational data and work region conditions to proactively adjust schedules before deviations occur, enabling adaptive response to changing conditions while maintaining systematic control through pre-established adjustment protocols
Data Source
AI summary
This disclosure provides an autonomous machine system having a scheduling controller configured to determine one or more windows of availability over a time period when the autonomous machine is allowed to operate to perform one or more operational tasks; determine a total operation time over the time period; and determine an operating schedule for a work region that assigns one or more operational tasks to the one or more windows of availability based on the total operation time. The autonomous machine may be commanded to operate in the work region according to the operating schedule.