Optimizing Industrial Robots for Accurate High-Speed Applications

Hubert Gattringer,Matthias Neubauer,Roland Riepl

doi:10.1155/2013/625638

Hubert Gattringer, Matthias Neubauer + Show 1 more

Open Access

https://doi.org/10.1155/2013/625638

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Abstract

Today’s standard robotic systems often do not meet the industry’s demands for accurate high-speed robotic applications. Any machine, be it an existing or a new one, should be pushed to its limits to provide “optimal” efficiency. However, due to the high complexity of modern applications, a one-step overall optimization is not possible. Therefore, this contribution introduces a step-by-step sequence of multiple nonlinear optimizations. Included are optimal configurations for geometric calibration, best-exciting trajectories for parameter identification, model-based control, and time/energy optimal trajectory planning for continuous path and point-to-point trajectories. Each of these optimizations contributes to the improvement of the overall system. Existing optimization techniques are adapted and extended for use with a standard industrial robot scenario and combined with a comprehensive toolkit with discussions on the interplay between the separate components. Most importantly, all procedures are evaluated in practical experiments on a standard robot with industrial control hardware and the recorded measurements are presented, a step often missing in publications in this area.

Highlights

State-of-the-art robotic systems are equipped with highly sophisticated industrial hardware, capable of short sample times and offering high computational power
The proper fundamentals are found in the underlying mathematical models. This contribution focuses on giving an overview of various nonlinear optimizations
The problem of optimal exciting trajectories is solved by nonlinear optimization techniques

Summary

Introduction

State-of-the-art robotic systems are equipped with highly sophisticated industrial hardware, capable of short sample times and offering high computational power This increasing arithmetic performance may be used to improve positioning accuracy and dynamic accuracy and compute time/energyoptimal trajectories. Applying all of them in sequence will provide better results regarding positioning accuracy and dynamic accuracy and will reduce the cycle times The basis for this optimization lies in the kinematic and dynamical modeling of the system. Previous works of the authors, which are focused on industrial robotics, see, for example, [1], cover the basics like control and geometric path planning Based on these works, a specific combination of algorithms is presented, each of which optimizes a specific aspect of the robotic system. Staubli RX130L industrial robot Degrees of freedom Maximum load capacity Reach at wrist Weight

System Modeling and Control

Static Position Accuracy

System Identification

Optimal Trajectory Generation

10 Figure 7

Conclusions