A Collaborative Control System for Telepresence Robots

Douglas Macharet and Dinei Florencio

Abstract

Interest in telepresence robots is at an all time

high, and several companies are already commercializing early

or basic versions. There seems to be a huge potential for their

use in professional applications, where they can help address

some of the challenges companies have found in integrating a

geographically distributed work force. However, teleoperation

of these robots is typically a difficult task. This difficulty can

be attributed to limitations on the information provided to the

operator and to communication delay and failures. This may

compromise the safety of the people and of the robot during its

navigation through the environment. Most commercial systems

currently control this risk by reducing size and weight of their

robots. Research effort in addressing this problem is generally

based on “assisted driving”, which typically adds a “collision

avoidance” layer, limiting or avoiding movements that would

lead to a collision. In this article, we bring assisted driving

to a new level, by introducing concepts from collaborative

driving to telepresence robots. More specifically, we use the

input from the operator as a general guidance to the target

direction, then couple that with a variable degree of autonomy

to the robot, depending on the task and the environment.

Previous work has shown collision avoidance makes operation

easier and reduce the number of collisions. In addition (and

in contrast to traditional collision avoidance systems), our

approach also reduces the time required to complete a circuit,

making navigation easier, safer, and faster. The methodology

was evaluated through a controlled user study (N=18). Results

show that the use of the proposed collaborative control helped

reduce the number of collisions (none in most cases) and also

decreased the time to complete the designated task.

Details

Publication typeInproceedings
Published in2012 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS’12)
PublisherIEEE
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