Real-Time Predictive Control of an UR5 Robotic Arm Through Human Upper Limb Motion Tracking

被引：5

作者：

Omarali, Bukeikhan ^{[1
]}

Taunyazov, Tasbolat ^{[2
]}

Bukeyev, Askhat ^{[3
]}

Shintemirov, Almas ^{[2
]}

机构：

[1] Nazarbayev Univ, NURIS, Sch Engn, 53 Kabanbay Batyr Ave,Z05H0P9, Astana, Kazakhstan

[2] Nazarbayev Univ, Sch Sci & Technol, 53 Kabanbay Batyr Ave,Z05H0P9, Astana, Kazakhstan

[3] Nazarbayev Univ, NURIS, Natl Lab Astana, 53 Kabanbay Batyr Ave,Z05H0P9, Astana, Kazakhstan

来源：

COMPANION OF THE 2017 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION (HRI'17) | 2017年

关键词：

Universal Robots UR5; real-time robot control; model predictive control; motion tracking;

D O I：

10.1145/3029798.3038918

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper reports the authors' initial results on developing a real-time teleoperation system for an Universal Robots robotic arm through human motion capture with a visualization utility built on the Blender Game Engine open-source platform. A linear explicit model predictive robot controller (EMPC) is implemented for online generation of optimal robot trajectories matching operator's wrist position and orientation, whilst adhering to the robot's constraints. The EMPC proved to be superior to open-loop and naive PID controllers in terms of accuracy and safety.

引用

页码：237 / 238

页数：2

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