Robotic Cell Skill Simulation Under Process Constraints
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Solution Overview
Problem
Current industrial automation systems face challenges in managing rapid innovation cycles, complex customization, and cost pressures, leading to a need for autonomy in factory floor operations, but lack effective methods to link autonomous skills with mechanical design and product design, resulting in inefficiencies and delays.
Innovation Solution
A computer-implemented method and system that utilizes a library of constructs and skills, combined with a simulation engine, to design and optimize the execution of processes by robotic cells, considering constraints such as speed and throughput, by simulating multiple designs and recommending feasible solutions that meet specified goals and constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional automation systems are used to maintain control and coordination, then system stability is preserved, but flexibility and adaptability to rapid innovation cycles are reduced
Solution Approach 1:
The system segments autonomous capabilities into reusable skill modules that can be independently developed, tested, and combined. Each skill represents a discrete autonomous capability that can be orchestrated to achieve complex goals without requiring centralized control of every detail.
Solution Approach 2:
The patent introduces an intermediary layer (skill orchestration system) that mediates between high-level autonomous skills and low-level robotic operations. This intermediary enables flexible task composition while maintaining system stability through standardized interfaces and coordination protocols.
2Productivity
If autonomous skills are implemented without systematic design methods, then innovation speed increases, but design efficiency and optimization are reduced
Solution Approach 1:
The system performs preliminary actions by pre-defining reusable skill modules and constructing virtual robotic cells in advance. These pre-prepared components can be quickly assembled and tested in simulation before deployment, significantly reducing commissioning time while maintaining design efficiency.
Solution Approach 2:
The patent enables parameter changes by allowing systematic adjustment of skill parameters, constraints, and performance metrics during the design and commissioning process. This facilitates optimization of autonomous systems for different applications without requiring complete redesign.
3Manufacturing precision
If virtual commissioning and simulation are performed extensively to optimize design, then design quality improves, but computational resources and time consumption increase
Solution Approach 1:
The system applies partial simulation actions by focusing computational resources on critical path skills and constraints rather than simulating every aspect of the robotic cell. This selective approach maintains design quality by thoroughly validating essential components while reducing overall simulation time through targeted analysis.
Data Source
AI summary
A computer-implemented method for designing execution of a process by a robotic cell includes obtaining a process goal and one or more process constraints. The method includes accessing a library of constructs and a library of skills. Each construct includes a digital representation of a component of the robotic cell or a geometric transformation of the robotic cell. Each skill includes a functional description for using a robot of the robotic cell to interact with a physical environment to perform a skill objective. The method uses a simulation engine to simulate a multiplicity of designs, wherein each design is characterized by a combination of constructs and skills to achieve the process goal, and determine a set of feasible designs that meet the one or more process constraints. The method includes outputting recommended designs from the set of feasible designs.