Billibon H. Yoshimi
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Ok. Ok. Enough with the clever kitch... on to the "Who am I?" and
"What do I do?" questions.
Who am I?
My name is Billibon Yoshimi.
FAQ 1: As you might have guessed, my first name is a
hybrid, Japanese-English name concocted by my father. Its actually
the concatination of my father's first name (Bon) and his best friend's
first name (William).
I was born in
Nebraska. I've spent part of my life living on a lake: Lake
Minitare, Nebraska. Most of my formative years were spent in
Scottsbluff though (6th grade-12th grade.)
In 1985, I attended Columbia University School of Engineering and
Applied Sciences. I majored in computer science and developed an
interest in human and robot vision.
Needless to say, in 1995, I finally finished my Ph.D. My
Visual Control of Robotic Tasks <1.4M>
, examines how vision systems can be integrated with robots. Or
basically, my thesis examines the issues faced by anyone wanting to
give a robot elementary eye-hand coordination skills.
In 1992, I designed a sensory
chessboard for the Deep Thought group at the IBM T. J. Watson Research Center.
Deep Thought is the reigning world electronic chess champion.
In 1995, I developed a complete audio interface to the world wide web
for the ATT
Applied Speech Research Lab in Murray Hill.
What are my research interests
- Vision guided robot control.
- Real-time vision systems.
- Active Contours (snakes).
- Virtual reality interfaces for haptic and tactile feedback.
- New interface for WWW browsing.
- Mobile Robotics and elementary reactive system.
Where to next?
After graduating from Columbia, I start as a Post-doctoral research
fellow at the National Institute of
Standards and Technology located in temperate Gaithersburg,
Clipping normally found on back of papers
Billibon H. Yoshimi is a graduate research assistant working under
Peter Allen in Computer Science at Columbia University. He received the
B.S., M.S., and Ph.D. degrees in Computer Science from Columbia University.
While at Columbia, he has
received several awards including the ARVO-National Eye Institute Travel
Award, the NCR Stakeholders Award, Columbia SEAS Bronze Key Award and an
Outstanding Student Award.
His current research interests include visually guided robot servoing,
real-time robotics, and real-time/parallel vision algorithms.
Billibon is also a member of IEEE.
Department of Computer Science
450 Computer Science Building
New York, New York 10027
(office) 1 212 939 7117
(fax) 1 212 666 0140
Billibon H. Yoshimi.
Visual Control of Robotic Tasks
Ph.D. Dissertation (1995)
Humans are at adept at eye-hand control. Robots are not. Even after
many hours of laborious programming, a robot's skill is only passable.
The goal of this thesis is to explore how vision can be used to give
robot systems the compliance and ability necessary to perform many
eye-hand coordination tasks. The thesis will describe the development
of three robot systems which examine how vision can be used to control
The first system addresses the role of vision in tracking and grasping
tasks. Since humans find little difficulty in visually tracking a
target and then effecting a grasp, we determined that the tracking and
grasping task was an appropriate vehicle to investigate the
application of vision to robot control. The experimental system is
composed of a real-time 3D motion stereo tracker, a robot-gripper
system capable of real-time tracking, and a set of grasping
strategies. The second system investigates how visual input can be
used to control an uncalibrated eye-hand system. This system performs
an alignment task by exploiting a simple observable geometric effect,
rotational invariance. Combined with image Jacobian-based control, this
system demonstrates that uncalibrated eye-hand control can be used in
situations where calibration is not available. The final
system re-examines the grasping and manipulation task. This system
exploits closed-loop visual feedback to control a robot and gripper as
they perform a complex task requiring dextrous manipulation.
The goal of this research program is to examine several fundamental
questions surrounding visual control. We will explore several
different way to perform visual control and find out where and when
they can be used. We will examine the suitability of vision for
real-time control. We hope to show visual control is a viable option
for performing real world tasks which require sensing in structured and
Billibon H. Yoshimi and Peter K. Allen.
Active, uncalibrated visual servoing.
In 1994 IEEE International Conference on Robotics &Automation, volume 4, pages 156-161, San Diego, CA, May 1994.
We propose a method for visual control of a robotic system which does not
require the formulation of an explicit calibration between image space and the
world coordinate system. Calibration is known to be a difficult and error
prone process. By extracting control information directly from the image, we
free our technique from the errors normally associated with a fixed
calibration. We demonstrate this by performing a peg-in-hole alignment using
an uncalibrated camera to control the positioning of the peg. The algorithm
utilizes feedback from a simple geometric effect, rotational invariance, to
control the positioning servo loop. The method uses an approximation to the
Image Jacobian to provide smooth, near-continuous control.
Billibon H. Yoshimi and Peter K. Allen.
Visual Control of Grasping and Manipulation Tasks,
In 1994 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems Las Vegas, NV, Oct 2-5, 1994.
This paper discusses the problem of visual control of grasping.
We have implemented an object tracking system that can be
used to provide visual feedback for locating the positions of fingers
and objects to be manipulated, as well as the relative relationships
of them. This visual analysis can be used to control open loop
grasping systems in a number of manipulation tasks where finger
contact, object movement, and task completion need to be monitored and
P. Allen, A. Timcenko, B. Yoshimi, and P. Michelman.
Automated tracking and grasping of a moving object with a robotic
IEEE Trans. on Robotics and Automation, 9(2):152-165, 1993.
Most robotic grasping tasks assume a stationary or fixed object. In this
paper, we explore the requirements for tracking and grasping a moving
object. The focus of our work is to achieve a high level of interaction
between a real-time vision system capable of tracking moving objects in 3-D
and a robot arm equipped with a dexterous hand that can be used pick up a
moving object. We are interested in exploring the interplay of hand-eye
coordination for dynamic grasping tasks such as grasping of parts on a
moving conveyor system, assembly of articulated parts or for grasping from
a mobile robotic system. Coordination between an organism's sensing
modalities and motor control system is a hallmark of intelligent behavior,
and we are pursuing the goal of building an integrated sensing and
actuation system that can operate in dynamic as opposed to static
environments. The system we have built addresses three distinct problems
in robotic hand-eye coordination for grasping moving objects: fast
computation of 3-D motion parameters from vision, predictive control of a
moving robotic arm to track a moving object, and grasp planning. The
system is able to operate at approximately human arm movement rates, and we
present experimental results in which a moving model train is tracked,
stably grasped, and picked up by the system. The algorithms we have
developed that relate sensing to actuation are quite general and applicable
to a variety of complex robotic tasks that require visual feedback for arm
and hand control.
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