Notice:This poster is associatedwith a Hands-On Demo

Haptic Teaching
using Opposite Force Presentation
Satoshi Saga* Naoki Kawakami* Susumu Tachi*(*) The University of Tokyo, Japan
E-mail: satoshi_saga@ipc.i.u-tokyo.ac.jp,{kawakami,tachi}@star.t.u-tokyo.ac.jp

1. Abstract
We propose a haptic teaching system that uses haptic devices
devices to teach hand skills.
Specifically, we chose some tasks with pencilpencil-like devices and examined how toteach an expert’
expert’s hand skills. We proposed a new haptic teaching method, in whichthe haptic device produces force that is in the opposite in direction. The trainee tries
tries
to cancel the force and consequently, necessary force is ‘‘proactively’’ generated.
‘‘proactively’’Our hypothesis is that this ‘‘proactiveness’’ is essential for haptic teaching. We‘‘proactiveness’’
made a prototype system and compared our methods with existing teachingteachingmethods.

Fig.1: Existing methods

2. Description

Expert’s Phase

Let FE and FT be output force of the expert and the trainee. ‘‘Proactive’’‘‘Proactive’’operation means that a trainee outputs the force that is necessary
necessary for operation andequal to the force FE. We propose the following methods to realize this situation.

Trainee’s Phase

Haptic Device

Haptic Device

Expert’expert’s model motion and force FE are recorded. The
Expert’s Phase: The expert’

Freacthaptic device with a tool attached at the tip is used as a measuring
measuring machine.

InverseInternalForceExpertReactionForce

FE Manipulate

TraineeFinv

FT Manipulate
Force

Force

Trainee’Trainee’s Phase: Following two methods are combined.

Virtual Trajectory

TrajectoryFvf

Virtual FixturesA) Opposite presentation of expert’s force along trajectory (Finv)• The haptic device generates the force that has the same amplitude
amplitude of the expert,
but in opposite direction.
direction. The trainee tries
tries to cancel the force andconsequently, necessary internal force is “proactively“proactively”” generated.

Fig.2: Proposed method

Finv = FE
FT = -F
Normal & Verticalto the trajectoryB) The utilization of Virtual Fixtures [2] orthogonal to the trajectory (Fvf )• Information of the expert’s motion is given (figure2(figure2), and the pathway is used
as a ruler by using Virtual Fixtures technique.

Normal & Horizontal
to the trajectory

Fvf = - k (xT - xE) 3

Tangential
to the trajectory

Trajectory

Fdisp = Finv + Fvf

Correlation of Force History

0.7

Existing Method
Proposed Method

0.6
0.5
0.4

0.3
We recorded force history data while subjects wrote “mirror reversed”
reversed” Greek
letters with both the proposed and existing methods. First, to estimate
estimate the effect of0.2
these methods, we calculate these correlations between the subject
subject’’s and expert’
expert’s
0.1
history data. Three components of the force (tangential, normal
normal vertical, normal
0horizontal part(Fig.4)) were separately evaluated. The result is shown in Fig.5.
TangentNormal & V
Normal & H
Each Force Direction
Through comparison, we found our method can transmit tangential and normal
horizontal force history to the trainee better than the existing method.
Fig.5: Correlations of force history

4. References[1] Gibson J.J.: Observations on active touch. Psychol.
Psychol. Rev, 69: pages 477477-491, 1962.
[2] L. Rosenberg. Virtual fixtures: Perceptual tools for telerobotic manipulation. In
Proc. of IEEE Virtual Reality Int’
Int’l. Symposium,Symposium, pages 76–76–82, 1993.
[3] Y. Kuroda, M. Nakao,Nakao, T. Kuroda, H. Oyama,Oyama, M. Komori and T. Matsuda,“Interaction Model between Elastic Objects for Accurate Haptic DisplayDisplay””,
International Conference of Artificial Reality and TeleTele-Existence (ICAT),(ICAT), pages.
148148-153, 2003
[4] C. L. Teo, E. Burdet,
Burdet, and H. P. Lim. A robotic teacher of Chinese handwriting. In
Proc. of 10th Symposium on Haptic Interfaces for Virtual Environment
Environment andTeleoperator Systems,Systems, pages 335–335–341, 2002.

0.36
0.35

Force Error(N/frame)

Second, we examine the learning effect of our proposed method andand existing
method by recording force history data between the iteration of practices. The resultis shown in Fig6. We found our method achieves some result in learninglearning tangential
force and normal horizontal force.

NormalVerticalForce Error

0.75

proposedexisiting

0.7

Force Error(N/frame)• [Existing method] (SlavedSlaved-Tracking Mode)
Mode)Passively
Passively following the expert’
expert’s positional information as presented by thehaptic device.

Fig.4: Separating force

Fig.3: System overview

TangentForce Error

0.65
0.6
0.55
0.5
0.45
0

proposedexisiting

10.34
0.33

0.44

0.32

0.42

0.31
0.3
0.29
0.28
0.27
01

2

34

5

67

Number of Trial(times)

23

4

5

Number of Trial(times)

67Force Error(N/frame)

The proposed method was compared with the following existing method,
method,through an experiment of letter writing tasks.

Correlation of Force History3. Experiment / Result

NormalHorizontalForce Error
proposedexisiting

0.4
0.38
0.36
0.34
0.32
0.3
012

34

5

Number of Trial(times)

Fig.6: Learning Curves of Each Force

67