Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nongeometric Errors

<table class="table-group" id="tab7"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left"> </td><td class="align_center">Mean (mm)</td><td class="align_center">Standard deviation (mm)</td><td class="align_center">Maximum (mm)</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">Before joint stiffness compensation</td><td class="align_center">7.0261</td><td class="align_center">1.2351</td><td class="align_center">10.0898</td></tr><tr><td class="align_left">After joint stiffness compensation</td><td class="align_center">0.9847</td><td class="align_center">0.5340</td><td class="align_center">2.4176</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Absolute positioning accuracy of the SIASUN SR210D manipulator.</div>

Complexity

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Table 7

Table 7: Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nongeometric Errors 

Table 7 | Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nongeometric Errors 