Accelerometer-Based Control of an Industrial Robotic Arm


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Abstract

Most of industrial robots are still programmed
using the typical teaching process, through the use of the robot
teach pendant. In this paper is proposed an accelerometer-based
system to control an industrial robot using two low-cost and
small 3-axis wireless accelerometers. These accelerometers are
attached to the human arms, capturing its behavior (gestures
and postures). An Artificial Neural Network (ANN) trained
with a back-propagation algorithm was used to recognize arm
gestures and postures, which then will be used as input in the
control of the robot.

INTRODUCTION

ROGRAMMING and control an industrial robot
through the use of the robot teach pendant is still a
tedious and time-consuming task that requires technical
expertise. Therefore, new and more intuitive ways for robot
programming and control are required. The goal is to
develop methodologies that help users to control and
program a robot, with a high-level of abstraction from the
robot specific language. Making a robotic demonstration in
terms of high-level behaviors (using gestures, speech,
manual/human guidance, from visual observation of human
performance, etc.), the user can demonstrate to the robot
what it should do [1]-[5].

SYSTEM OVERVIEW

A. System Description
The demonstration cell (Fig. 1) is composed of an
industrial robot MOTOMAN HP6 equipped with the NX100
controller, two 3-axis wireless accelerometers to capture
human hand behaviors, and a computer running the
application that manages the cell.
The 3-axis accelerometers (ADXL330, Analog Devices)
are physically rated to measure accelerations over a range of
at least +/- 3g, with a sensitivity of 300 mV/g and sensitivity
accuracy of 10%. The accelerometers communicate with the
computer via Bluetooth wireless link, reporting back data at
100 Hz (Fig. 2).

CONTROL STRATEGY

A. Robot Control
The robot is controlled remotely via the Ethernet using a
command that moves the robot linearly according to a
specified pose increment [ ]T
i = i1 i2 i3 i4 i5 i6 . The
first three components represent the robot translation along
the X, Y and Z axes, respectively, whereas the last three
components represent the robot rotation about the X, Y and
Z axes, respectively. These components i have the necessary
information to control the robot. It is therefore necessary to
identify them by examining the behavior of the user right
arm.

CONCLUSION AND FUTURE WORK

Due to the growing demand for natural Human Machine
Interfaces and robot intuitive programming platforms, a
robotic system that allows users to control an industrial robot
using arm gestures and postures was proposed. Two 3-axis
accelerometers were selected to be the input devices of this
system, capturing the human arms behaviors. When
compared with other common input devices, especially the
teach pendant, this approach using accelerometers is more
intuitive and easy to work, besides offering the possibility to
control a robot by wireless means. Using this system, a nonexpert
robot programmer can control a robot quickly and in a
natural way.