Robot Motion Node Splitting for Conflict-Free Schedule Planning
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Solution Overview
Problem
Robotics planning requires extensive manual programming, which is time-consuming, error-prone, and incompatible across different workcells, making it difficult to predict task completion times and adapt schedules to varying robotic environments.
Innovation Solution
A system that uses process definition graphs and transformers to split and combine motion nodes, allowing for automated generation of robotics schedules that eliminate conflicts and optimize task efficiency, reducing manual programming requirements and enabling flexible scheduling across different workcells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual programming is used to generate robotic schedules, then the schedule can be customized for specific workcells, but the process becomes time-consuming, error-prone, and incompatible across different workcells
Solution Approach 1:
The patent uses process definition graphs as reusable templates that can be copied and adapted across different workcells. Instead of manually programming each workcell from scratch, the system creates a standardized graph structure that represents robotic processes, which can then be instantiated and modified for various workcell configurations, eliminating repetitive manual programming while maintaining adaptability
Solution Approach 2:
The system allows dynamic modification of process definition graphs by changing parameters such as motion nodes, conflict regions, and scheduling constraints. By adjusting these parameters rather than rewriting entire schedules, the system can adapt to different workcells efficiently, reducing both time loss and improving compatibility across diverse robotic environments
2Reliability
If manual programming meticulously dictates robotic movements, then task completion can be achieved, but the process is tedious, error-prone, and makes it difficult to predict completion times
Solution Approach 1:
The patent segments the robotic scheduling problem into distinct components represented as nodes in a process definition graph, including motion nodes, task nodes, and conflict regions. This segmentation allows each component to be analyzed and optimized independently, reducing programming complexity while maintaining reliable task completion through systematic composition of validated segments
Solution Approach 2:
The process definition graph serves as an intermediary structure between high-level task requirements and low-level robotic movements. This intermediate representation layer automates the translation process, reducing programming complexity and errors while improving predictability of task completion times through structured transformation rules
3Productivity
If a schedule is manually generated for one workcell, then it can be optimized for that specific environment, but it cannot be used for other workcells with different robots, numbers of robots, or physical dimensions
Solution Approach 1:
The patent creates a universal process definition graph framework that can serve multiple workcell configurations. The graph structure incorporates parameterized elements that can be instantiated for different numbers of robots, various physical dimensions, and diverse task requirements, allowing a single optimized framework to serve multiple specific workcells while maintaining both productivity and adaptability
4Device complexity
If motion nodes are kept as single unified paths, then the schedule is simpler to manage, but conflicts between robot paths cannot be effectively resolved
Solution Approach 1:
The patent segments motion nodes into multiple sub-paths when conflicts are detected, dividing a single motion node representing a conflict-prone path into several smaller motion nodes that can be scheduled independently. This segmentation resolves conflicts by allowing temporal and spatial separation of potentially conflicting movements while maintaining overall schedule manageability through the structured graph representation
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing a plan for one or more robots using a process definition graph. One of the methods includes receiving a process definition graph for a robot, the process definition graph having a plurality of action nodes. One or more of the action nodes are motion nodes that represent a motion to be taken by the robot from a respective start location to an end location. It is determined that a motion node satisfies one or more splitting criteria, and in response to determining that the motion node satisfies the one or more splitting criteria, the process definition graph is modified. Modifying the process definition graph includes splitting the motion node into two or more separate motion nodes whose respective paths can be scheduled independently.