ROSYMar 12, 2021

Offset-free Model Predictive Control: A Ball Catching Application with a Spherical Soft Robotic Arm

arXiv:2103.07379v1
Originality Incremental advance
AI Analysis

This enables more accurate control for soft robotics applications, such as ball catching, but is incremental as it builds on existing model predictive control methods.

The paper tackled the problem of controlling a spherical soft robotic arm by developing an offset-free model predictive controller that compensates for model deviations, reducing tracking error by 35% compared to a standard controller without disturbance compensation.

This paper presents an offset-free model predictive controller for fast and accurate control of a spherical soft robotic arm. In this control scheme, a linear model is combined with an online disturbance estimation technique to systematically compensate model deviations. Dynamic effects such as material relaxation resulting from the use of soft materials can be addressed to achieve offset-free tracking. The tracking error can be reduced by 35% when compared to a standard model predictive controller without a disturbance compensation scheme. The improved tracking performance enables the realization of a ball catching application, where the spherical soft robotic arm can catch a ball thrown by a human.

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