3D gaze cursor: continuous calibration and end-point grasp control of robotic actuators
File(s)
Author(s)
Marcos Tostado, P
Abbott, WW
Faisal, AA
Type
Conference Paper
Abstract
Eye movements are closely related to motor ac-
tions, and hence can be used to infer motor intentions. Ad-
ditionally, eye movements are in some cases the only means
of communication and interaction with the environment for
paralysed and impaired patients with severe motor deficiencies.
Despite this, eye-tracking technology still has a very limited
use as a human-robot control interface and its applicability is
highly restricted to 2D simple tasks that operate on screen based
interfaces and do not suffice for natural physical interaction
with the environment. We propose that decoding the gaze
position in 3D space rather than in 2D results into a much
richer "spatial cursor" signal that allows users to perform
everyday tasks such as grasping and moving objects via gaze-
based robotic teleoperation. Eye tracking in 3D calibration is
usually slow – we demonstrate here that by using a full 3D
trajectory for system calibration generated by a robotic arm
rather than a simple grid of discrete points, gaze calibration in
the 3 dimensions can be successfully achieved in short time and
with high accuracy. We perform the non-linear regression from
eye-image to 3D-end point using Gaussian Process regressors,
which allows us to handle uncertainty in end-point estimates
gracefully. Our telerobotic system uses a multi-joint robot arm
with a gripper and is integrated with our in-house "GT3D"
binocular eye tracker. This prototype system has been evaluated
and assessed in a test environment with 7 users, yielding gaze-
estimation errors of less than 1cm in the horizontal, vertical and
depth dimensions, and less than 2cm in the overall 3D Euclidean
space. Users reported intuitive, low-cognitive load, control of the
system right from their first trial and were straightaway able
to simply look at an object and command through a wink to
"grasp this" object with the robot gripper.
tions, and hence can be used to infer motor intentions. Ad-
ditionally, eye movements are in some cases the only means
of communication and interaction with the environment for
paralysed and impaired patients with severe motor deficiencies.
Despite this, eye-tracking technology still has a very limited
use as a human-robot control interface and its applicability is
highly restricted to 2D simple tasks that operate on screen based
interfaces and do not suffice for natural physical interaction
with the environment. We propose that decoding the gaze
position in 3D space rather than in 2D results into a much
richer "spatial cursor" signal that allows users to perform
everyday tasks such as grasping and moving objects via gaze-
based robotic teleoperation. Eye tracking in 3D calibration is
usually slow – we demonstrate here that by using a full 3D
trajectory for system calibration generated by a robotic arm
rather than a simple grid of discrete points, gaze calibration in
the 3 dimensions can be successfully achieved in short time and
with high accuracy. We perform the non-linear regression from
eye-image to 3D-end point using Gaussian Process regressors,
which allows us to handle uncertainty in end-point estimates
gracefully. Our telerobotic system uses a multi-joint robot arm
with a gripper and is integrated with our in-house "GT3D"
binocular eye tracker. This prototype system has been evaluated
and assessed in a test environment with 7 users, yielding gaze-
estimation errors of less than 1cm in the horizontal, vertical and
depth dimensions, and less than 2cm in the overall 3D Euclidean
space. Users reported intuitive, low-cognitive load, control of the
system right from their first trial and were straightaway able
to simply look at an object and command through a wink to
"grasp this" object with the robot gripper.
Date Issued
2016-06-20
Date Acceptance
2016-05-16
Citation
2016 IEEE International Conference on Robotics and Automation (ICRA), 2016, pp.3295-3300
Publisher
IEEE
Start Page
3295
End Page
3300
Journal / Book Title
2016 IEEE International Conference on Robotics and Automation (ICRA)
Copyright Statement
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Source
IEEE International Conference on Robotics and Automation (ICRA)
Publication Status
Published
Start Date
2016-05-16
Finish Date
2016-05-21
Coverage Spatial
Stockholm