Robot Joint Reducer Selection Using Backlash Simulation
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Solution Overview
Problem
The challenge in robot manufacturing lies in selecting reducers that balance backlash, which affects robot performance, while avoiding high costs associated with smaller backlash reducers and potential unsmooth operation from larger backlash reducers.
Innovation Solution
A method to quantify backlash-induced gaps in robot joints through simulation, determining suitable reducer types based on motion deviation data, optimizing cost by choosing reducers with larger backlash that meet performance requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reducers with smaller backlash are adopted, then robot performance is improved, but total cost increases
Solution Approach 1:
The patent changes the parameter of backlash from a fixed design constraint to a variable that can be optimized through simulation. By modeling different backlash values and their effects on robot performance, the system identifies the minimum acceptable backlash threshold, allowing selection of cost-effective reducers that meet performance requirements rather than always choosing the smallest backlash (highest cost) option.
Solution Approach 2:
The patent performs preliminary simulation and evaluation of backlash effects before the actual reducer selection and manufacturing process. By conducting virtual experiments to determine the relationship between backlash and robot performance in advance, the system establishes selection criteria that guide the choice of reducers, avoiding costly trial-and-error in the actual manufacturing and operation phases.
2Ease of manufacture
If low-priced reducers with larger backlash are adopted, then cost is reduced, but robot operation becomes unsmooth
Solution Approach 1:
The patent transforms the qualitative assessment of operation smoothness into a quantitative analysis by simulating robot operation with different backlash values. The system identifies the threshold at which backlash begins to degrade operation smoothness, enabling selection of reducers with the largest acceptable backlash that still maintains smooth operation, thus optimizing cost while preserving operational quality.
Solution Approach 2:
The patent implements a feedback mechanism where simulation results regarding operation smoothness are used to adjust and refine the backlash selection criteria. By evaluating how different backlash values affect operation smoothness in the simulation environment, the system provides feedback that guides the selection of reducers, ensuring that cost-effective options do not compromise operational smoothness beyond acceptable limits.
3Adaptability or versatility
If the influence of reducer backlash is difficult to measure, then selection becomes uncertain, but manufacturing process complexity increases
Solution Approach 1:
The patent introduces a simulation system as an intermediary between the reducer selection decision and the actual robot performance. This simulation intermediary models the relationship between backlash and robot performance, allowing indirect assessment of backlash effects without requiring complex physical measurement systems. The simulation acts as a virtual testbed that simplifies the selection process while maintaining accuracy.
Solution Approach 2:
The patent replaces complex physical measurement and testing systems with computational simulation. Instead of using elaborate experimental setups to measure and evaluate backlash effects on actual robots, the system uses software-based simulation to predict performance outcomes. This substitution dramatically reduces the complexity of the manufacturing process while maintaining or improving selection accuracy.
Data Source
AI summary
A robot joint configuration determining method, a robot using the same, and a computer readable storage medium are provided. The method includes: simulating a joint model of a first joint of the robot using first motion deviation data to obtain first result data; simulating the joint model using second motion deviation data to obtain second result data; taking the motion deviation data corresponding to one of the first result data and the second result data meeting one or more preset conditions as a target motion deviation data for the first joint; and determining type information of a reducer in a configuration information of the first joint based on the target motion deviation data. In the present disclosure, the motion deviation of the first joint that is relatively accurate can be obtained through the results of the two simulations.