Stable Haptic Interaction with Virtual EnvironmentsUsing an Adapted Voxmap-PointShell Algorithm

Matthias Renz1,2, Carsten Preusche1, Marco Pötke2, Hans-Peter Kriegel2, Gerd Hirzinger1

Abstract

Despite a lot of research in recent years stable andrealistic haptic interaction with virtual environmentskeeps an unsolved problem. Among different approachesthe Voxmap-PointShellTM (VPS) method seems verypromising due to constant sample rates, independent ofthe static environment. But there is still the stabilityproblem to be solved globally. In this paper someadaptations based on the VPS are presented, includingthe dynamic object modeling and the force calculationmethod, to reduce the distractions of the calculatedcollision forces to increase stability. The PointShell pointslie exactly on the surface of the dynamic object, to get asmoother surface representation. A variation of thecollision force calculation leads to a reduction of the“voxel noise”, that appears due to the discretization ofthe volume space. A design framework for the virtualcoupling is presented, that enables the automaticconfiguration for different haptic devices. The validitywill be shown with different kineasthetic hand controllers.

1. Introduction

There are numerous haptic rendering algorithms forvirtual simulations, differing in object and surfacemodeling. Object models are mostly approximatedescriptions of the simulated objects, used in the virtualenvironment. In many rendering algorithms, thegeometrical complexity of the particular modeled objectsis restricted due to high rendering times. In the VPSapproach of McNeely, Puterbaugh and Troy [6], thevirtual environment consists of objects divided intodynamic and static objects. Dynamic objects can freelymove through the virtual space, whereas the static objectsare fixed in the world coordinate system. With a hapticdevice, a human can touch the static objects (static

environment) with the dynamic object, and the renderedcollision forces will be fed back to the operator.

The haptic rendering update rate is independent fromthe complexity of the static environment, thus qualifyingfor real time applications. The environment of staticobjects is collectively represented by a single spatialoccupancy map called a voxmap (volume map). This iscreated by discretizing the static environment space,which is partitioned into regions of free space, objectsurface, and object interior. The collection of the discretevolume elements (voxels) build the voxmap. The dynamicobject is described by a collection of points (PointShell),which models its surface. Each point is assigned a surfacenormal vector, pointing inwards. The haptic renderingalgorithm includes a fast collision detection techniquebased on probing the voxmap with the surface pointsamples of the PointShell. By using the normal vectors ofthe PointShell, an approximate collision force can beeasily computed in constant time for each point-voxelinterpenetration. Figure 1 shows a PointShell collidingwith the voxmap. For each PointShell point, contained bya surface voxel, the depth of interpenetration is calculatedas the distance d from the point to the tangent plane. Thisplane passes through the voxel center and has the samenormal vector as the PointShell point normal vector.

originalobjects Point Shell

Voxmap

d

force vector alongpoint normal

TangentPlane

PointShell

Static Surface

Figure 1: Voxmap-PointShell-ModelTM

1 German Aerospace Center (DLR)Institute of Robotics and MechatronicsOberpfaffenhofen, D-82234 Weßling

renz@robotic.dlr.de,Carsten.Preusche@dlr.de, Gerd.Hirzinger@dlr.de

2 University of MunichInstitute for Computer Science

D-80538 Munich

poetke@informatik.uni-muenchen.de,kriegel@informatik.uni-muenchen.de

Proceedings of the Eurohaptics Conference, Birmingham, UK, 2001

So the time consumed to render a single frame dependsonly on the number of PointShell points. The real timecapability qualifies this algorithm for online hapticinteractions between a human operator and a virtualenvironment. For enhancing haptic stability, McNeely etal. [6] employ a ‘virtual coupling’ scheme, whichconnects the user’s haptic motion with the motions of thedynamic object through a virtual spring and damper. Thisscheme was embedded in the haptic rendering algorithm.But mechanical properties of different haptic devices arenot treated by this virtual coupling, and it is difficult totune the system to obtain a stable haptic feedback.

In contrast, the approach described in this paperdecouples the stability problem from the haptic rendering,as also proposed by Adams and Hannaford [1], where thevirtual coupling was treated as part of the haptic interface(device and virtual environment). This allows the usage ofan arbitrary haptic rendering algorithm independent fromthe haptic device. Almost no changes of the virtualenvironment parameters are required, when the hapticdevice changes. In chapter 2, we present adaptations tothe VPS based object modeling and force calculation, forreducing the distractions of collision forces to get morestability. The ‘virtual coupling’ is described in chapter 3.Chapter 4 shows some results of experiments, where thevalidity of the methods can be seen. The paper closes withthe conclusion in chapter 5.

2. Extending the VPS Algorithm

2.1 Exact PointShell Creation

The calculation of the contact force takes place in theforce voxel layer which is one voxel deep. Due to thedesign of the VPS method the effective force layer deptharound static objects amounts to half a voxel. So it can beseen easily, that surface deviations of the PointShellobject, with an amplitude of more then a half voxel size,have considerable influence on force distractions. Thissurface variance appears due to the PointShell creationdescribed in the original VPS, where the object first wasvoxelized, and the collection of all surface voxel centersbuild the PointShell (Fig. 3, 1-3).

Next, the extended PointShell creation is presented,where the points lie on the triangulated object surface(anti-aliasing), not only to improve the accuracy, but alsoto stabilize the collision force. The example in Figure 2shows the same collision situation of a dynamic and staticobject, with the two different PointShell models. In theupper scene (Fig. 2 a), the PointShell was built with theoriginal algorithm, where the distance between the

PointShell points and the object surface is up to e2

3,

where e denotes the voxel extension. This surfacedeviation is very high compared to the force layer depth

of e/2. In the case of Figure 2 a) the PointShell wascreated using the voxel raster shown with dashed lines.With this rough surface approximation only one of thefour PointShell points effects a collision force, althoughthe ‘real’ dynamic object surface cross three force layervoxel. Figure 2 b) shows the effected collision forcesusing the exact PointShell model, creating a smootherforce field.

The exact PointShell creation process steps are shownin Figure 3. The first two steps are equal to the originalPointShell creation. In order to guarantee a properdetection of collisions between dynamic and staticobjects, the distance between two neighbored PointShellpoints is limited according to the voxel resolution of thestatic environment. Hence the ‘naive’ PointShell is builtby the sum of all center points of the resulting surfacevoxels, after creating the VoxMap of the dynamic objectwith the same resolution as of the static environment (Fig.3, 1-3).

A smoother surface representation can be achieved byprojecting each center point on to the triangle surface

Figure 3: Steps of the exact PointShellcreation algorithm

1 2 3

4 5 6

Figure 2: Different collision force effects incomparison between the originalPointShell and our exact Point Shell

exact PointShell

dynamic object surface

Voxel raster for PointShell creation

Pointshellpoints

active force vectors

original PointShell

b)

a)

e

force voxel layer

object interior voxel

(Fig. 3, 4-5). Two additional requirements for the newposition have to be fulfilled:

1) inside the primary voxel2) minimal distance to the voxel center

This two requirements can be inconsistent with oneanother, whereas the first requirement has the higherpriority and the second should be optimized as far aspossible. The first condition keeps the maximal neighborpoint distance such that an unrecognized interpenetrationof the static and dynamic object is prevented. Theextension of the spatial gap between two PointShell pointneighbors is restricted to the minimal spatial extension ofa static object surface part (3 voxel extensions, if a forcefield is used as described by McNeely [6]). The propertyof the shortest distance tries to keep the original distanceof the point neighborhood as far as the other conditionsallows, for a convenient point distribution.

Algorithm: The following algorithm shows the correctpoint-surface-projection, keeping the above requirementswith the defined priority. The object surface is describedby a number of triangles. Due to the condition, that theprojected point must be contained by the respective voxel,only the triangles with a common intersection point withthat voxel have to be considered. For each triangle thefollowing steps have to be done. First calculate from thevoxel center the perpendicular nadir p0 on the trianglesurface. Now four cases have to be considered:

Let:- V be the set of all points contained by the respective

Voxel;- VS be the set of all points lying on the surface of the

respective Voxel; VS ⊆ V;- T be the set of all points lying on the observed triangle;

then:case 1: p0 ∈ V and p0 ∈ T:

the result is p0;case 2: p0 ∈ V and p0 ∉ T:

return point pr ∈ {T ∩ V}, which has theshortest distance to p0;

case 3: p0 ∉ V and p0 ∈ T:return point pr ∈ {T ∩ VS}, which has theshortest distance to p0;

case 4: p0 ∉ V and p0 ∉ T:if (pr ∈ T with the shortest distance to p0) ∈ V

then the result is pr,else the result is equal to the result of case 3;

Figure 4 shows two examples of case 4. The treatmentin case 4 is generally valid, therefore all cases can behandled by the following algorithm:

For each original PointShell point (voxel center), mapit on the corresponding triangles, and choose the resultpoint with the shortest distance to the voxel center. Theset of all mapped points build the exact PointShell. Nowthe PointShell vectors can be calculated from the normaldirections of the triangles intersecting the relevant voxel.

2.2 Adapted Collision Force Calculation

Further force discontinuities appear, when PointShellpoints cross static voxel borders. Especially under slidingmotion with a relatively constant interpenetration betweenthe dynamic and static object, this effect, shown in Figure5 (a, b), causes instability and notably disturbs theoperator’s correct sense of touch (vibrations). Thepresented variation of the VPS collision force calculation[6], leads to smoother transitions at voxel borders. Incontrary to hierarchical methods, which increase thecalculation time, the presented method does not need afiner resolution (granularity) of the static environment.

Instead of providing a general solution to the forcestability problem, our adapted force calculationspecifically targets the force noise for dynamic objects

Algorithm :

projectPoint(Voxel, Triangle)p0 = perpendicularNadir(Voxel.centerpt, Triangle.plane);pr = trianglePointWithShortestDistanceToPoint(p0);if (Voxel.contains(pr))then return(pr)else intersection_lines = intersect(Triangle, Voxel.surface);

for each Line ∈ intersection_lines pl = linePointWithShortestDistanceToPoint(p0,Line); presult = min(distance(pl,p0), distance(presult,p0));

return presult;end;

Triangle plane

Voxel

Voxelcenter

Zoom area

Triangle

result point(lying on voxelsurface)

perpendicularnadir p0

result point(lying inside thevoxel)

Figure 4: Two examples showing theprojection treatment of case 4

sliding over a plane of adjacent surface voxels. WhenPointShell points cross the border between these adjacentvoxels, instability occurs if the direction of the relevantpoint normal vector is not perpendicular to the slidingplane. Figure 5 a) shows a dynamic object colliding witha static object under sliding motion. Figure 5 b) and c)demonstrate the interesting area (marked with the dashedline in 5 a)). Figure 5 b) shows the problem that appearswith the original force calculation method. When thePointShell point crosses the voxel border, the calculatedforce value is reduced to zero, which influences theoverall collision force. Instead of using the individualPointShell normals to calculate the collision force, theaverage of all collision point normals is used to calculatethe interpenetration distance d of each PointShell point(Figure 5 c)). This average direction is a more stableapproximation of the sliding plane normal, and thementioned problem can be mitigated.

3. Virtual Coupling

The schemes described above only reduce force noise,but there are still remaining distracting forces causing anunstable system. The direct way to reach the requiredstability is to use a ‘virtual coupling’ scheme between theoperator and the virtual environment. A design frameworkfor the virtual coupling is presented, that allows aconsistent interaction between the haptic rendering (VPS)and different haptic devices, because for the overallstability, the dynamic properties of the haptic device playa key role.

In many other approaches (e.g. McNeely et al. [6],Adams and Hannaford [1]) the virtual coupling is treatedand parameterized as a spring-damper system, which is agood mechanical interpretation, but leads in most cases toa heuristic optimization of the parameters. The spring-

damper system is used to reduce the force steps, producedby discontinuities and discretization, for the human user.

The virtual coupling can also be seen as a dynamicshaping filter, as it is done in this approach (Fig. 6). Thedynamics of the calculated contact force are reduced suchthat neither the haptic device nor the force reflection loopwith the human become unstable.

Filter Construction

The filter should keep the role of the virtual coupling,thus the physically model of the virtual coupling (thespring-damper system) is used as a model for theconstruction part.

With this mechanical representation (Fig. 7) thefollowing equation can be built:

xmxrxcF &&& ⋅+⋅+⋅=

For the filter, the translation value x must be replacedby the collision force as input, which is generated by thehaptic rendering algorithm. This replacement can be doneunder the condition that the collision force dependsdirectly on the penetration distance, which is true withthis haptic rendering algorithm (Fcoll ~ xpos (collision)).

With c

mT = ,

Tw

10 = ,

cm

rd

⋅=

2,

cK

1=

this function leads to the PT2-element with the followingtransfer function (continuous time):

20

20

20

2)(

sswdw

wKsH f +⋅⋅⋅+

⋅=

The continuous time filter can be transformed to thediscrete time filter Hf(z) with the Tustin-Approximation:

1

12

+−⋅=

z

z

Ts

A

,

21

21

21

1

020

20

)1(

)1(4

1

122

)(

−

−

−

−

+−

⋅++−⋅⋅⋅⋅+

=

z

z

Tz

z

Twdw

wKzH

AA

f

x F

massmc

r

Figure 7: Mechanical spring-damper system

Figure 5: Force stabilization under sliding motion

a)

dynamic object surfacewith PointShell points

interestingarea

force voxellayer

sliding motiondirection

c)

tangent planenext objectposition

b) without with

adapted force calculation

current objectposition

Figure 6: Signal flow diagram of the hapticsimulation

hapticdevice

dynamicshaping

filter

Ffeedback Fcoll

xpos

Fh

xh

hapticrendering

human

The parameters used with this filter function can easilyadjusted to the dynamic properties of the haptic device,without changes in the haptic rendering algorithm.Whereas the sample time TA is chosen by the cycle timeof the rendering algorithm and haptic device, thesufficient stability can be reached by adjusting the cut-off-frequency w0 and the damping factor d.

Typically a human can sense kineasthetic impressionwith a bandwidth of approximately 1kHz [3] and canmake controlled movements with a maximal bandwidth of10 Hz. Studies at the DLR resulted in a bandwidth of 2Hz in which a human performs a desired task (noreflexes). To perceive realistic kineasthetic impression thedynamic of the force controller (implemented at thedevice) plays the key role and limits the achievablebandwidth. That means that the force dynamic of thevirtual environment can be limited to 5Hz without loosinga realistic impression of the scene.

4. Experiments

The validity will be shown in experimental resultsusing the Phantom T-Model (Fig.14) and the DLR- lightweight robot (Fig. 13) as kineasthetic hand controller [7].In the virtual test bed the static scene consists of a cup,whereas a sphere is used as dynamic object manipulatedby the operator (Fig 15).

4.1 Experiments to the Adapted Collision ForceCalculation

For a benchmark of the force distractions, the resultsof the collision force calculations are evaluated in twoexperiments. The dynamic sphere was moved over thestatic object with a predefined path and a constantpenetration. The experiments differ with respect to thesurface conditions of the static object, which typicallyoccur in discrete space models like the voxel map. Thesurface condition depends on the orientation of thesurface plane related to the main axis planes of the voxelgrid coordinate system. Force distractions, appearing insliding motion, primarily influence the collision forcedirection. For demonstrating this effect, only the forceparts vertical to the collision plane normal (the intuitivecollision force direction) were recorded. In eachexperiment this record is done for both the original andthe adapted collision force calculations. The directcomparison between them is depicted in the followingdiagrams, made for each experiment.

Experiment 1: sliding motion over a plane surfaceThe sliding path of the dynamic object is in thisexperiment a circle movement over a plane surface of thestatic object. In Figure 8 all the distraction arrowheads are

recorded, by keeping the axis origin at the sphere centerposition.

In the experiment related to Figure 8 a) and b) thesliding surface of the static object was oriented along thevoxel grid main axes, whereas 8 c) and 8 d) presents theresults of the motion over a not voxel grid raster orientedplane. With the adapted force calculation the distractionreduction is appreciable in both cases.

Experiment 2: sliding motion over a curved surfaceIn this experiment the sphere slides on a circle patharound the superficies surface of a cylinder, with also aconstant penetration depth into the cylinder (Fig. 10). Thisshows the collision force distraction behavior with manydifferent surface condition cases. Figure 9 a) shows thedistractions of the collision force over the time calculatedwith the original algorithm and Figure 9 b) shows thedistractions with the adapted algorithm. Of cause there arestill remaining distractions with the adapted form comingfrom the different surface conditions, but a high reductionof these distractions can be seen with the adaptedcollision force calculation.

Figure 9: Collision force distractions in onedirection of experiment 2

ba

Figure 10: Benchmark for the virtual coupling

Figure 8: Collision force distractions ofexperiment 1

a)

b)

c)

d)

0 200 400 600 800 1000

−0.1

−0.05

0

0.05

0.1

0.15Force distraction Plot (with adaptation)

Frame Number

Z d

irect

ion

0 200 400 600 800 1000

−0.1

−0.05

0

0.05

0.1

0.15Force distraction Plot (without adaptation)

Frame Number

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irect

ion

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Y d

irect

ion

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Y d

irect

ion

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−0.05

0

0.05

0.1

0.15Force distraction Plot (without adaptation)

X direction

Y d

irect

ion

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−0.1

−0.05

0

0.05

0.1

0.15Force distraction Plot (with adaptation)

X direction

Y d

irect

ion

4.2 Experiments to the Virtual Coupling

To evaluate the virtual coupling, a sphere is movedover a cylindrical static object with a constant penetration(Fig. 10).

In Figure 11 shows the results of a heuristic tunedvirtual coupling and the dynamic shaping filter explainedin chapter 3. In hardware-in-the-loop experiments, thevirtual cup (Fig. 15) was touched by the virtual sphereusing the DLR Light-Weight robot (LWR) (Fig. 13) andthe Phantom T-Model (Fig. 14) as haptic hand controllers.The following diagrams (Fig. 12) shows the collisionforces (thin line) calculated by the haptic renderingalgorithm and the corresponding output force (thick line),which was returned as feedback force to the handcontrollers by the virtual coupling element. Two kinds ofcollisions were tested, an abrupt collision, hitting the cupwith the sphere (Fig. 12 a,c), and a steady collision,sliding with the sphere over the cup surface (Fig. 12 b,d).

5. Conclusions

In this paper some efforts were done to improve thestability and immersion of haptic feedback. Our approachis based on the VPS method, due to its constant samplerates. First the object modeling was improved towards anexact surface representation. This not only increases theaccuracy, but also avoids some force distractions duringcontact situation with static objects. The force calculationitself was adapted such that the voxel noise, occurringduring sliding motions over static objects, is substantiallyreduced. This leads to a smoother force evolution within

the task. Finally, a design framework for virtual couplingwas presented. It takes into account the dynamicproperties of the human operator and of the handcontroller. This approach leads to a more stable hapticinteraction with virtual environments as it is shown in thepresented experiments.

Further work in the fields of improving the realistichaptic feedback extending the VPS, and of automaticdesign of the virtual coupling will be done.

6. References

[1] R. J. Adams, B. Hannaford, “Stable Haptic Interactionwith Virtual Environments”, Proc. IEEE Transactionson Robotics and Automation, vol. 15, no. 3, June 1999,pp. 465-474.

[2] K. J. Aström, B. Wittenmark, Computer-ControlledSystems: Theory and Design, 3rd ed., Prentice-Hall,Inc., 1997, NJ, ISBN 0-13-314899-8.

[3] G. Burdea, Force and Touch Feedback for VirtualReality, John Wiley Sons, Inc., 1996.

[4] O. Föllinger, Regelungstechnik: Einführung in dieMethoden und ihre Anwendung. 7th ed., Hüthig, 1992,Heidelberg, ISBN 3-7785-2136-5.

[5] T. Massie, K. Salisbury, “The PHANToM HapticInterface: A Device for Probing Virtual Objects”,Proc. ASME Winter Annual Meeting, Symposium onHaptic Interfaces for Virtual Environments andTeleoperator Systems, Chicago, IL, November 1994

[6] W. A. McNeely, K. D. Puterbaugh, J. J. Troy, “SixDegree-of-Freedom Haptic Rendering Using VoxelSampling”, Proc. ACM SIGGRAPH, 401-408, 1999.

[7] C. Preusche, R. Koeppe, A. Albu-Schäffer, M. Hähnle,N. Sporer, G. Hirzinger: “Design and Haptic Controlof a 6 DoF Force-Feedback Device”, In: Proc. of the2001 Workshop on Advances in InteractiveMultimodal Telepresence

[8] C.B. Zilles, J.H. Salisbury, “A Constraint Based God-Object Method for Haptic Display”, Proc. IEEE Conf.on Intelligent Robots and Systems, vol 3, 1995, pages146-151

Figure 13:DLR Light-Weight robotas kineasthetic handcontroller

Figure 15:Virtual test bed

Figure 14:Phantom T-Modelfrom SensableTechnologies Inc.

a) b)

c) d)

Figure 12: Force plots of the experiments withthe Phantom and the LWR

Figure 11: Force plots for different virtualcouplings

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5

10

15

20

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30LWR Force Plot (abrupt collision)

cycle number

For

ce [N

]

output force collision force

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24.77

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cycle number

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rce

[N

]

output force collision force

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7Phantom Force Plot (abrupt collision)

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10Phantom Force Plot (sliding motion)

cycle number

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output force collision force

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6Force with dynamic shaping filter

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]

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]