Model Predictive Force Control for Robots in compliant Environments with guaranteed Maximum Force | IEEE Conference Publication | IEEE Xplore

Model Predictive Force Control for Robots in compliant Environments with guaranteed Maximum Force


Abstract:

In this paper, we propose a model predictive force controller, which ensures that the force the object in an unknown environment exerts on the robot is limited by a user-...Show More

Abstract:

In this paper, we propose a model predictive force controller, which ensures that the force the object in an unknown environment exerts on the robot is limited by a user-defined value. The environment is assumed compliant and during movement, the internal model of the environment is constantly updated. This update is performed using position and force information. The information of past measurements is stored in a memory function in the form of additional constraints for the MPC. The proposed controller is tested in simulation where it has to overcome both convex and nonconvex obstacles in an unknown environment.
Date of Conference: 10-12 July 2019
Date Added to IEEE Xplore: 29 August 2019
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Conference Location: Philadelphia, PA, USA

I. Introduction

Robots performing tasks in poor visibility environments, such as sewers or the human body in the case of minimal invasive surgeries, have to rely on information other than cameras. Soft continuum robots equipped with a position and force sensor, operating in an unknown environment, motivate this paper.

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