Hand Gesture Recognition and Tracking Control for a Virtual UR5 Robot Manipulator

Human-machine interfaces (HMIs) have received an increased attention during the past decades, specially due to the use of robots in many fields of the industry. In this paper, we employ a hand gesture recognition (HGR) system and the inertial measurement unit (IMU) integrated in the Myo Armband sensor as a HMI to control the position and orientation of a virtual six-degree-of-freedom (DoF) UR5 robot. As part of the HMI, this work also focuses on solving the trajectory tracking problem for the UR5 robot using two different control strategies: a minimum norm PID and a controller based on linear algebra. Both controllers are designed from the UR5 kinematic model. Finally, we test and compare their performance by computing their IAE performance criterion and the position errors obtained from two experiments: tracking pre-defined input trajectories and commanding the virtual robot by the HGR system plus the Myo Armband's IMU signals.

I. Introduction

In the last decades, the use of robotic manipulators have been spreading in many applications such as intervention in hazardous environments, robotic surgery, prosthetics, industrial assembly, among others [1]. In these scenarios, the human operator is often essential, especially in unstructured environments where the automation of robot actions can be a complex task. In this context, the development of human-machine interfaces (HMIs) can help to increase the performance, versatility and teleoperation in the field of robotic manipulators. Several HMIs have been studied to control these mechatronic platforms by using different interface devices such as keyboards, joysticks, inertial measurement units (IMUs) [2], cameras [3], Kinect sensors [4], haptic devices [5], and electromyography (EMG) based systems [2], [6]. In fact, the control of manipulators that uses advanced sensors such as EMG-based hand gesture recognition (HGR) systems is still an open research problem.