Human-manipulator interface using particle filter.

Guanglong Du,Ping Zhang,Xueqian Wang

doi:10.1155/2014/692165

Guanglong Du, Ping Zhang + Show 1 more

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https://doi.org/10.1155/2014/692165

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Abstract

This paper utilizes a human-robot interface system which incorporates particle filter (PF) and adaptive multispace transformation (AMT) to track the pose of the human hand for controlling the robot manipulator. This system employs a 3D camera (Kinect) to determine the orientation and the translation of the human hand. We use Camshift algorithm to track the hand. PF is used to estimate the translation of the human hand. Although a PF is used for estimating the translation, the translation error increases in a short period of time when the sensors fail to detect the hand motion. Therefore, a methodology to correct the translation error is required. What is more, to be subject to the perceptive limitations and the motor limitations, human operator is hard to carry out the high precision operation. This paper proposes an adaptive multispace transformation (AMT) method to assist the operator to improve the accuracy and reliability in determining the pose of the robot. The human-robot interface system was experimentally tested in a lab environment, and the results indicate that such a system can successfully control a robot manipulator.

Highlights

Human intelligence is required to make a decision and control the robot especially when it is in unstructured dynamic environments
This paper proposes Camshift to track the human hand and particle filter (PF) to estimate the position of the hand, as well as an adaptive multispace transformation method to improve the accuracy and efficiency of manipulation
The time from the beginning to the first circle is the period of approaching the object

Summary

Introduction

Human intelligence is required to make a decision and control the robot especially when it is in unstructured dynamic environments. For completing a teleoperation task, these contacting mechanical devices always require unnatural hand and arm motion There is another way to communicate complex motions to a remote robot and it is more natural compared with using contacting mechanical devices. This method uses inertial sensors, contacting electromagnetic tracking sensors, gloves instruments with angle sensors, and exoskeleton systems [5] to track the operator hand-arm motion which completes the required task. These contacting devices may hinder natural human-limb motion

Methods

Results

Conclusion