Robotic Cell Design Using Autonomous Skill Constraint Feedback
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Solution Overview
Problem
Existing systems fail to effectively integrate autonomous skill performance feedback into the mechanical design of robotic cells, leading to delays and inefficiencies due to siloed decision-making and lack of visibility across design teams.
Innovation Solution
A computer-implemented method and system that utilizes a simulation module to generate and recommend optimal designs for robotic cells by combining skills and mechanical constructs, leveraging high-fidelity simulation and machine learning to meet specified constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous systems are implemented to increase flexibility and reduce human involvement, then adaptability and productivity are improved, but decision-making complexity and design coordination difficulty increase
Solution Approach 1:
The system segments the autonomous skill execution into discrete, evaluable components. The simulation module evaluates individual skill executions and generates separate feedback signals for each skill, allowing independent optimization and analysis of each autonomous function rather than treating the entire system as an undifferentiated whole.
Solution Approach 2:
The simulation module acts as an intermediary between autonomous skill execution and mechanical design optimization. It receives skill performance data, processes it through high-fidelity simulation, and generates design recommendations that bridge the gap between operational feedback and design decisions, reducing the complexity of direct coordination.
2Manufacturing precision
If high-fidelity simulation and comprehensive evaluation are performed to optimize design, then manufacturing precision and reliability are improved, but computation time and processing resources increase
Solution Approach 1:
The system performs preliminary high-fidelity simulation and evaluation during the design phase rather than during actual operation. By pre-evaluating multiple design scenarios and generating recommendations before implementation, the system achieves high precision optimization without incurring computation time penalties during production operations.
Solution Approach 2:
The simulation module performs evaluation on representative skill instances and critical path skills rather than exhaustively evaluating every possible skill execution. This partial evaluation approach provides sufficient design optimization accuracy while significantly reducing computation time and resource requirements.
3Productivity
If constraints are added to optimize performance and throughput, then productivity is improved, but design complexity and evaluation difficulty increase
Solution Approach 1:
The system implements feedback loops where simulation results and skill performance measurements are fed back into the design optimization process. The simulation module continuously evaluates design alternatives against throughput constraints and provides feedback recommendations, allowing iterative refinement that achieves high productivity while managing design complexity through systematic evaluation.
Data Source
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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.