Rule Execution Engine for Adaptive Robotic Workcells
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Solution Overview
Problem
Manual programming of robotic movements is tedious, time-consuming, and error-prone, and schedules generated for one workcell are often incompatible with different workcells due to unique physical constraints.
Innovation Solution
An execution system utilizing a knowledge-based system with an execution engine subsystem and an execution memory subsystem, which processes fact updates efficiently and drives robotic movements based on relevant rule conditions, allowing for real-time adjustments and compatibility across varying workcell environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual programming is used to dictate robotic movements, then precise control of robotic components is achieved, but the programming process becomes tedious, time-consuming, and error-prone
Solution Approach 1:
The system enables robots to autonomously generate and adjust their own movement schedules based on sensor observations and rule-based reasoning, eliminating the need for manual programming. The execution system automatically processes facts about the workcell environment and triggers appropriate actions without human intervention, making the system self-sufficient in adapting to different workcells.
2Manufacturing precision
If manual programming is used to create schedules for a specific workcell, then precise control for that workcell is achieved, but the schedule becomes incompatible with other workcells having different physical properties
Solution Approach 1:
The execution system is designed as a universal platform that can operate in any workcell environment. It uses sensor-rich observations and rule-based reasoning to adapt to different physical properties, robot configurations, and workcell layouts. The same system architecture handles diverse scenarios from automotive assembly to food preparation without requiring workcell-specific programming.
Solution Approach 2:
The system dynamically adjusts its behavior based on real-time sensor observations and the specific characteristics of each workcell. Rather than using fixed manual schedules, the execution system continuously processes facts about the environment and adapts its control strategies to match the current workcell's physical properties and constraints.
3Reliability
If comprehensive monitoring of robotic operations is implemented to detect faults and contingencies, then system reliability is improved, but the complexity of processing online observations increases
Solution Approach 1:
The execution system segments the complex task of monitoring and fault detection into manageable components. It separates the processing of sensor observations from the execution of actions, using a rule-based architecture where different rules handle different aspects of monitoring. This modular approach makes the complex monitoring function more tractable and maintainable.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for rule execution in an online robotics system. One of the systems includes an execution engine subsystem and an execution memory subsystem. The execution engine receives rules having types and subtypes that represent a particular entity in an operating environment of a robot, provides subscription requests to the execution memory subsystem, and receives events emitted by the execution memory subsystem. The an execution memory receives subscription requests from the execution engine subsystem, receives new observations, converts the new observations into fact updates, performs pattern matching with the fact updates against the patterns of the subscription requests, and emits events to the execution engine subsystem for patterns that have been matched by the fact updates.