Semi-Autonomous Robot Teleoperation with Obstacle Avoidance via Model Predictive Control

被引：0

作者：

Rubagotti, Matteo ^{[1
]}

Taunyazov, Tasbolat ^{[2
]}

Omarali, Bukeikhan ^{[3
]}

Shintemirov, Almas ^{[1
]}

机构：

[1] Nazarbayev Univ, Dept Robot & Mechatron, Astana, Kazakhstan

[2] Natl Univ Singapore, Dept Comp Sci, Singapore, Singapore

[3] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London, England

来源：

ROBOTICS: SCIENCE AND SYSTEMS XV | 2019年

关键词：

MANIPULATORS;

D O I：

暂无

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

This paper(1) proposes a model predictive control approach for semi-autonomous teleoperation of robot manipulators: the focus is on avoiding obstacles with the whole robot frame, while exploiting predictions of the operator's motion. The hand pose of the human operator provides the reference for the end effector, and the robot motion is continuously replanned in real time, satisfying several constraints. An experimental case study is described regarding the design and testing of the described framework on a UR5 manipulator: the experimental results confirm the suitability of the proposed method for semi-autonomous teleoperation, both in terms of performance (tracking capability and constraint satisfaction) and computational complexity (the control law is calculated well within the sampling interval).

引用

页数：8

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