Multi-Robot Plan Scheduling for Resource and Continuity Constraints
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Solution Overview
Problem
Efficiently scheduling complex tasks among multiple robots or devices in manufacturing and other applications is challenging due to resource constraints, spatial conflicts, and continuity requirements, which existing technologies struggle to address effectively.
Innovation Solution
A computer system that determines candidate plan elements for each task, defines constraint profiles including resource, spatial, and continuity constraints, and uses a constrained programming solver to select and sequence plan elements to optimize task completion time, energy use, and material conservation, allowing for concurrent execution without synchronization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple robots are used to perform complex tasks concurrently, then productivity increases, but resource conflicts and spatial constraints increase
Solution Approach 1:
The patent segments complex tasks into discrete plan elements with defined constraints. Each plan element represents a schedulable unit with specific resource requirements, spatial constraints, and continuity conditions. This segmentation enables the scheduling system to manage multiple robots independently while coordinating their actions through constraint-based selection and sequencing of plan elements.
2Manufacturing precision
If plan elements are scheduled with strict time synchronization, then coordination precision improves, but scheduling flexibility decreases
Solution Approach 1:
The patent employs continuity constraints to ensure that plan elements execute without disruptive breaks. Instead of rigid time synchronization, the system maintains continuity by aligning end states of one plan element with beginning states of the next, allowing flexible timing while ensuring proper coordination. This enables the system to adapt to variable execution times while maintaining operational integrity.
3Reliability
If constraint profiles are defined for all plan elements, then scheduling robustness improves, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by defining constraint profiles for all candidate plan elements before the actual scheduling process. These pre-defined constraint profiles include resource requirements, spatial constraints, and continuity conditions. By preparing these constraints in advance, the system enables efficient constraint-based selection and sequencing during execution, reducing real-time computational burden while maintaining robustness.
4Productivity
If the system optimizes for minimum completion time, then productivity increases, but resource consumption increases
Solution Approach 1:
The patent allows the scheduling system to select from multiple candidate plan elements for each task, where different plan elements represent different trade-offs between completion time and resource consumption. The constraint-based selection process can choose plan elements that provide partial optimization rather than aggressive minimization, allowing the system to balance speed with energy efficiency based on specific operational requirements.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for scheduling resource-constrained actions. In some implementations, data indicating a set of tasks to be performed by a group of multiple robots is received. A set of candidate plan elements is determined for each task in the set of tasks. A constraint profile for each of the candidate plan elements is generated, where each of the constraint profiles indicates a constraint to be satisfied in order to carry out the corresponding candidate plan element. Plan elements configured to perform each of the tasks in the set of tasks are selected based on the constraint profiles, and assembled into a schedule according to optimization criteria. This schedule can be used to perform tasks, and the schedule may account for variability in timing without failure.