Autonomous Machine Scheduling for Adaptive Work Region Maintenance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing autonomous grounds maintenance machines lack efficient scheduling mechanisms that adapt to changing conditions without requiring user input, leading to inefficiencies in maintaining work regions.
Innovation Solution
The development of autonomous machine functionality that determines an operating schedule for maintaining a work region, allowing for adaptive scheduling based on changing conditions, using sensors and navigation systems to ensure proper maintenance without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous machines operate without scheduling mechanisms, then user input is minimized, but maintenance efficiency and adaptability to changing conditions deteriorate
Solution Approach 1:
The autonomous machine performs self-scheduling by automatically determining when and where to execute maintenance tasks based on sensor data and environmental conditions, eliminating the need for external user input while maintaining high productivity through intelligent self-management
Solution Approach 2:
The system continuously monitors environmental conditions, machine status, and task completion through sensors, using this feedback to dynamically adjust and optimize the operating schedule, thereby improving maintenance efficiency while remaining fully autonomous
2Ease of operation
If fixed operating schedules are used, then scheduling simplicity is improved, but adaptability to changing conditions deteriorates
Solution Approach 1:
The operating schedule transitions from a static fixed plan to a dynamic adaptive schedule that automatically adjusts task timing and routing based on real-time environmental conditions, machine status, and priority levels, maintaining simplicity while improving adaptability
Solution Approach 2:
The system modifies schedule parameters such as task timing, routing, and priority based on changing environmental conditions and machine state, enabling the schedule to adapt dynamically without requiring complex user reconfiguration
3Reliability
If user input is required for scheduling, then schedule accuracy is improved, but operational complexity and user burden increase
Solution Approach 1:
The machine autonomously generates and adjusts its own maintenance schedule by processing sensor data and environmental information, achieving high schedule accuracy without requiring external user input or complex user-facing scheduling interfaces
Solution Approach 2:
The system replaces manual user-based scheduling with an automated electronic control system that uses sensors, processors, and algorithms to determine optimal maintenance timing and routing, reducing user burden while maintaining or improving schedule accuracy
Data Source
Figure 1
Figure 2A
Figure 2B
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.