Artificial Neural Network Guided Compensation of Nonlinear Payload and Wear Effects for Industrial Robots

Author:

Raible Julian1,Rettig Oliver2,Alt Benjamin3,Yaman Alper1,Gauger Isabelle1,Biasi Lorenzo1,Müller Silvan2,Katic Darko3,Strand Marcus2,Huber Marco F.1

Affiliation:

1. Institute of Industrial Manufacturing and Management IFF, University of Stuttgart,Stuttgart,Germany,70569

2. Baden-Württemberg Cooperative State University,Karlsruhe,Germany,76133

3. ArtiMinds Robotics GmbH,Karlsruhe,Germany,76131

Funder

Federal Ministry of Education and Research

Publisher

IEEE

Reference37 articles.

1. Simultaneous identification of joint compliance and kinematic parameters of industrial robots

2. Pybotics: Python Toolbox for Robotics

3. Positioning Accuracy Improvement of Industrial Robots Considering Configuration and Payload Effects Via a Hybrid Calibration Approach

4. Kinematic calibration of a collaborative robot by a marker based optical measurement procedure;rettig;Proceedings of the 17th International Conference on Intelligent Autonomous Systems IAS-17 IAS Society Ed,2022

5. Calibration of industry robots with consideration of loading effects using product-of-exponential (poe) and gaussian process (gp);jing;2016 IEEE International Conference on Robotics and Automation (ICRA),0

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