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Controlling a Passive Haptic Master During Teleoperation Ph.D. Proposal by Benjamin A. Black January 28, 2005 Intelligent Machine Dynamics Laboratory George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology

Controlling a Passive Haptic Master During TeleoperationControlling a Passive Haptic Master During Teleoperation Ph.D. Proposal by Benjamin A. Black January 28, 2005 Intelligent Machine

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Page 1: Controlling a Passive Haptic Master During TeleoperationControlling a Passive Haptic Master During Teleoperation Ph.D. Proposal by Benjamin A. Black January 28, 2005 Intelligent Machine

Controlling a Passive Haptic MasterDuring Teleoperation

Ph.D. Proposalby

Benjamin A. Black

January 28, 2005

Intelligent Machine Dynamics LaboratoryGeorge W. Woodruff School of Mechanical Engineering

Georgia Institute of Technology

Page 2: Controlling a Passive Haptic Master During TeleoperationControlling a Passive Haptic Master During Teleoperation Ph.D. Proposal by Benjamin A. Black January 28, 2005 Intelligent Machine

Abstract

The primary goal of the research proposed here is to develop a control scheme for passive haptic de-vices used as a master device during teleoperation. Haptic, or force-feedback devices can be dividedinto two groups based on the energetic nature of their actuators, either passive or active. The researchhere studies the passive devices, more specifically dissipative passive devices that use brakes to gen-erate forces by removing energy from the system. As a whole, haptic devices have an ever growing listof applications that includes the remote control of another device, called teleoperation. The researchproposed here will focus further on the use of passive haptic devices in teleoperation.

Work thus far has applied a classic (active haptic) teleoperation control scheme to the system. Thepreliminary results show the shortcomings of the classic control when applied to a passive device,thereby highlighting the need for the development of a different control scheme.

The end goal of the research will focus on the two aspects of the control scheme, the algorithmfor calculating the haptic force and the actual force generation. A control scheme will be designedspecifically to provide haptic feedback on a passive device. Further, the research will investigate andverify the limitations of force generation in a passive device. Without this verification, even the mostrobust algorithm for force calculation proves useless.

Page 3: Controlling a Passive Haptic Master During TeleoperationControlling a Passive Haptic Master During Teleoperation Ph.D. Proposal by Benjamin A. Black January 28, 2005 Intelligent Machine

Contents

1 Introduction 1

2 Literature Review 12.1 Teleoperation & Haptics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 Human Factors Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.3 Other Relevant Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

3 Proposed Research 3

4 Preliminary Analysis 34.1 Force Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

4.1.1 On-Off Actuation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54.1.2 Multi-Brake Actuation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74.1.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

4.2 Force Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

5 Preliminary Experiments 115.1 Master Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115.2 Slave Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115.3 Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115.4 Initial Testbed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115.5 CRS Robot Testbed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

6 Proposed Work 136.1 Advanced Force Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136.2 Extension of Hardware and Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146.3 Plan For Proceeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

7 Contributions 15

8 Acknowledgments 15

References 16

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List of Figures

1 The drawing shows the configuration of the planar passive haptic master. Note that jointsA, B & E are actuated while joints C & D are not. . . . . . . . . . . . . . . . . . . . . . . . 4

2 The three single degree of freedom paths created by locking brakes A, B & E as well asthe possible forces generated by each brake . . . . . . . . . . . . . . . . . . . . . . . . . 5

3 Variables used for control calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Variables and demonstration of the principle used in calculating the average angle error . 75 The average angle error over the workspace using single brake actuation . . . . . . . . . 76 Angle error graphs for multi-brake actuation . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Endpoint forces over the workspace caused by unit actuation of each the three individual

brakes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Endpoint forces over the workspace caused by unit actuation of the three individual

brakes and a photo of the overall teleoperation system . . . . . . . . . . . . . . . . . . . . 109 The master-slave system in photographic, screenshot and line drawing form . . . . . . . . 1210 Results of the experiment using the CRS robot to drive MR PTER . . . . . . . . . . . . . 13

List of Tables

1 Results from constant force test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 Position error from the CRS robot test (%of workspace) . . . . . . . . . . . . . . . . . . . 12

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1 Introduction

In a very general sense, haptic devices are designed to provide a human user with the ability to physi-cally interact with either a virtual or remote environment. The word ”haptic” refers to the sense of touch,and therefore a haptic robotic device augments a user’s sensory feedback by providing or tactile physicalsensory information.

Haywood compares the development of haptic devices to the development of the computer moni-tor [1]. A blank piece of paper provides very little sensory information other than the fact that it is apiece of paper. When encoded with information we interpret the black or colored marks as text andlanguage. However a printed sheet of paper can display only one fixed set of information. In a similarway, a traditional computer input device such as a mouse yields little physical information to the user(other than size, shape, inertia, and some friction), and none of that information acts as an output fromthe computer. Compared to a piece of paper, a computer monitor encodes information no differently butallows that information to be changed dynamically to represent different information. Similarly, hapticdevices allow the physical sensory information being returned to the user to be programmed, controlledand changed dynamically. In the case of haptic devices, the sensory information is tactile instead ofvisual. Furthermore, instead of being a one-way flow of information as with the computer screen, hap-tic devices typically represent both an output from and an input to a computer. The devices dubbed”digital clay” perfectly represent this analogy in that they behave like a 3-D input / output device for acomputer [2].

Haptic devices have found a long list of useful applications, and they extend in size from micro-scale [3] to the workspace of automobile assembly [4], and their scope covers applications from surgeryassistance [5][6] to handling of hazardous materials [7]. One of the more interesting uses of a hapticdevices is teleoperation, or remote control. In this, a remote, or ”slave” device is controlled by a haptic”master” device. The user interacts with the remote environment through the master and the slavedevices. Forces from the remote system are transmitted to the human user through the actuation of themaster device.

Haptic devices can be categorized by the energetic nature of their actuators, either active or pas-sive. Active devices comprise the larger portion of haptic interfaces currently in use and are actuatedby active components such as motors, hydraulics, pneumatics, etc. The much less common groupof passive devices are actuated with components such a brakes, clutches or Continuously VariableTransmissions (CVTs). Devices using CVTs redirect energy and are energetically neutral, while devicesthat use clutches and brakes have the ability to dissipate energy through friction and are subsequentlydeemed dissipative passive haptic devices. Realistically all devices dissipate some energy, but dissipa-tive passive devices control and use that dissipation to produce haptic forces.

2 Literature Review

2.1 Teleoperation & Haptics

Haptic devices owe their history to the study of teleoperation. In a sense, haptic devices that interfaceonly with a computer are still teleoperating a virtual device. As referenced by Hayward [1], the lineage ofthe modern teleoperator can be traced to the research of Goertz in the mid 1950s [8] and his hydraulicteleoperators used to handle radioactive material. The discussion of the physical information beingdisplayed to the user (a concept that developed into haptics) began in the 1980s with the research ofBejczy in the Jet Propulsion Lab [9] and the work of Sherrick in 1985 [10]. From a psychological pointof view, the early research of Klatzky and Bajcsy in 1987 and 1991 explored the ability of a user to feeland identify virtual objects using a haptic device [11] [12].

Possibly most relevant to the work here is the haptic control concept of passivity and its use in guar-anteeing stability[13][14]. Hannaford and Ryu developed a haptic control law that specifically addresspassivity [15]. An adaptation of impedance control, the software implementation of passivity can guar-

1

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antee stability of the haptic device and thus the safety of the human user by never allowing the outputenergy of the device to be positive. Ruy further extended time-domain passivity to teleoperation sys-tems by injecting damping into the haptic device to insure that it only dissipates energy [16]. Similarapproaches for stability and safety have been developed by Lee and Li [17][18][19][20] who produceda control law that relaxes the required knowledge about the remote system model and moves toward amore robust control system.

The idea of passivity has also been extended to teleoperation as an attempt to handle network de-lay. Instead of communicating in terms of force and velocity, a system using wave variables appliespassivity theory by transforming the input and outputs of the system in a way such that control vari-ables are energy terms. Passivity is then insured if the power in is more than or equal to the powerout. Anderson and Spong introduced the use of wave variables to handle network time-delay in hapticteleoperation [21]. Niemeyer and Slotine extend this research slightly and present theories on adaptivecontrol of haptic devices [22] [23]. Current research at Georgia Tech. extends upon these basics byadding predictors [24]

In the above examples of passivity-based control, the energetic nature of the device is enforcedthrough software. Even an active haptic system can be forced to remain passive by reading sensorvalues and calculating output through the control scheme such that no energy is generated by thedevice. In contrast, haptic devices with passive actuators insure passivity through the constraints oftheir hardware and are therefore more fault-tolerant.

As previously mentioned, passive haptic systems include both energetically neutral and energeticallydissipative devices. Colgate et. al have explored the use of energetically neutral haptic devices thatuse continuously variable transmissions (CVTs) as actuators that neither dissipate energy from nor addenergy to the system [25][4][26][27][28]. The devices are capable of producing very stiff virtual surfaces,one method for judging a haptic device [29]; however, in free motion, they require processing and cantherefore lag.

Dissipative devices produce forces by resisting user motion and dissipating energy. Compared tothe devices built around CVT actuators, dissipative devices have more difficulty producing stiff virtualsurfaces, but perform much better in free motion. Cho’s analysis of these devices produced the con-cept of the Force Manipulability Ellipsoid as a description of a haptic device’s capabilities within theworkspace [30]. Gao and Book extended this and developed the concept of steerability, a passivehaptic device’s ability to redirect motion[31][32].

Few passive haptic devices currently exist. Other than the two devices developed through previousresearch at Georgia Tech (to be discussed shortly), only two or three can be found. Sakaguchi devel-oped a planar device using electro-rheological (ER) brakes and a belt / pulley system to increase theirforce output [33]. Matsuoka has developed the only 3-DOF device with publications, a large-workspacedevice intended to guarantee user-safety [34]. Finally, Wannasuphoprasit has presented a design fora planar passive device using linear pneumatic cylinders (like controllable car shocks) but nothing hasbeen published about its completion [35].

At Georgia Tech, two dissipative devices have been used for research, both developed under Book.Charles developed the first device, PTER, that used friction brakes and clutches to actuate its joints [36].Impedance control of the device was explored by Gomes [37] as well as Swanson, who also developed avelocity field control used in path following haptic experiments [38]. Reed improved the hardware by de-veloping MR PTER, a re-configurable planar device using magneto-rheological brakes for actuation [39].He then applied the velocity field path following control to the device [40].

2.2 Human Factors Research

In addition to the mechanical and controls research that applies to the history of haptic robotics, thehuman element of the system must also be explored. Some of the earliest human factors testing camefrom Fitts in the early 1950’s. Not only did he found the theories that still drive user interface design [41],he also looked at the human behavioral response to stimuli [42], the basis of the understanding of how

2

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to influence a human user with haptic feedback.In the more recent past, the idea of human cognitive modeling has impacted the field of human-

computer interaction research. Lochart and Murdock applied principles of signal detection theory tolook at decision making based on stimuli [43]. The early 80’s saw the introduction of the Human ModelProcessor (HMP) [44] out of which the study of human cognitive architecture was born. The theoriesthat developed out of the HMP attempted to fit the structure of human cognition into a block diagramform to mimic the architecture of a computer. In a sense, this architecture creates a limited human modelthat produces an output action or performance given an input set of conditions. The ACT architecturedeveloped by Anderson [45] and extended by Byrne [46] as well as the EPIC architecture developed byKieras & Meyer [47] represent the most widely accepted cognitive models.

2.3 Other Relevant Work

The research proposed here also shows some similarity in a control sense to the research of Boniventoand Melchiorri [48][49][50]. The research involves producing haptic feedback using a wire actuatedmanipulator. Unlike other wire-driven devices, the wires are not set up in balancing pairs. Therefore atany point in the workspace, single-directional discrete forces can be generated by each wire. Melchiorriand Bonivento demonstrated the abilities of this style of a device as a portable haptic interface.

Haptic devices have found an interesting niche in the field of medical instrumentation. In additionto the typical training devices, haptic devices are now being applied to surgical procedures themselveswhether that be remotely performed surgeries, or haptically enhanced surgeries. Quaid applies a hapticdevice as a surgical assistance during bone sculpting in orthopedic surgery [6]. Similarly, Rossi &Boschetti, explore the use of haptic devices to assist during neurosurgery and spine surgery [51][52].In both of these cases, the active device used provides assistance to the human surgeon by sharingcontrol of the tool.

3 Proposed Research

The focus of the research presented here will be centered around using a dissipative passive hapticdevice during teleoperation. Due to the energetic nature of dissipative haptic devices, arbitrary forcescannot be generated. Instead, forces can only be generated that oppose the motion of the user. Thisin turn means that traditional algorithms for generating force feedback during teleoperation will not workas they would in an active system.

The central issue of the research addresses how to produce helpful haptic feedback that aides ahuman in completing a task while keeping in mind the constraints of the passive system. The productionof haptic forces can be divided into two portions, the generation of forces with a passive haptic deviceand the determination of the haptic forces to be displayed to the human operator. The research willaddress both issues. For that reason, the research section of the report will be also divided into thosetwo sections.

The final goal of the research presented here will be to develop a set of tools to discuss and comparea passive haptic device’s ability to act as a master during teleoperation. In that, driving factors will beidentified for development of a control scheme, and human testing will be completed to verify all of thework. The steps and process to achieve these results will be discussed in brief detail in the sectionentitled ”Proposed Work.”

4 Preliminary Analysis

Thus far, work on this project has centered mainly around the generation of forces using a passivehaptic device. Once an acceptable scheme is developed for producing forces, the focus can then shift

3

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Link 1

Link 3

Link 4

Joint A & B

Joint E

Joint D – handle

Joint C

Link 2

Workspace Boundary

θAθB

Figure 1: The drawing shows the configuration of the planar passive haptic master. Note that joints A,B & E are actuated while joints C & D are not.

to developing an algorithm used to define and calculate the forces that are to be displayed to the humanuser. The work thus far will be described in the following section, divided into force generation andforce calculation. The analysis will begin with a discussion of the force generation so that when thediscussion turns to algorithms for calculating the haptic force, the framework will be set to understandthe limitations of passive devices.

4.1 Force Generation

Passive haptic devices are inherently handicapped in that they cannot produce arbitrary forces. Theycan only produce forces that oppose motion of a user or oppose the input force of a user when thevelocities go to zero. It is important to understand the limitations of the system’s force generation to beable to understand and develop a control scheme.

Two actuation schemes will be presented here and compared based on their ability to generate aforce in an arbitrary direction. MR PTER will be used in the discussion and development of the controlscheme to provide a visual representation of the theories discussed; however these principles can beapplied to any passive haptic device. The configuration of MR PTER can be seen in Fig. 2(a). MRPTER is a planar parallelogram-shaped manipulator (re-configurable to be a 5-link device in which thebase joints are not coaxial) with brakes actuating base joints A & B as well as joint E. The base anglesθA and θB , are measured using encoders. The human interfaces with the device through a handle anda 6-DOF force / torque sensor at joint D.

Locking a brake of the passive master will force the device to move along a single degree of freedomcircular path. At any point in the workspace of MR PTER, there exist three such single DOF paths, thedirections of which are shown in Fig. 3(a) for a specific configuration. The directions are labeled

⇀pA,

⇀pB

&⇀pE to represent the paths created by locking brakes A, B & E, and the directions are guaranteed to be

unique by physically preventing the device from entering a singular configuration.At any given place in the workspace, the force produced by a specific brake is perpendicular to the

single DOF path that would be generated by locking that brake. The force can point either toward thecenter of rotation or away from the center of rotation depending on the endpoint velocity. Figure 2(b)shows the direction of forces at the same device configuration as shown in Fig. 2(a). The forces are

labeled⇀

fA,⇀

fB &⇀

fE in the negative and positive direction to represent all possible directions of forcethat can be generated by the individual brakes A, B & E.

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pE

pApB

(a) Single DOF Paths

fE

fA fB

v

−fB

−fE

−fA

(b) Single DOF Forces

fE

fB

v

fA

fh2

fh1

(c) Possible Brake Forces with aDefined Velocity

Figure 2: The three single degree of freedom paths created by locking brakes A, B & E as well as thepossible forces generated by each brake

The forces generated at the endpoint of the manipulator cannot increase endpoint velocity. Doing sowould violate passivity in that a force component in the direction of motion would increase the system’senergy. With the endpoint velocity shown in Fig. 2(b), the dashed vectors represent forces that cannotbe generated. The region of

⇀v ±π

2 defines the region of un-producible forces. This region is visible inFigs. 2(b) & 2(c) as the vertical line through the endpoint.

From here forward, the discussion will deal with forces only when the input direction is known, and

will be labeled only as⇀

fA,⇀

fB &⇀

fE to represent the forces generated by actuating brakes A, B & E.Furthermore, from here forward it will be assumed that the force to be displayed to the user is called⇀

fh, the haptic force. The calculation of⇀

fh will be discussed in the next section. Actuation schemes

only apply if⇀

fh is at least π2 radians from the direction of

⇀v . Note that as the velocity slows to zero,

calculation of⇀v becomes indeterminate, and the control ceases to function properly. In practice, below

a specific velocity magnitude, the control switches and uses the direction of force input in the controlcalculations. The rationale is that direction of force input to the system at or near zero velocity representsthe direction of impending motion. All of this rationale assumes a quasi-static state of the system. Thusfar, the dynamics have been ignored.

4.1.1 On-Off Actuation

In the simplest actuation scheme, the brake that produces a force closest in direction to⇀

fh is actuated.

In Fig. 2(c), brake A would be actuated for the haptic force direction⇀

fh1, and brake B would be actuated

for force direction⇀

fh2. Work has been done exploring the achievable results using this control schemein a simple test [53]. The results of this experiment will be discussed further in the following sections.

This single brake actuation scheme can only produce forces in unique directions, basically discretiz-ing the force generation to the number of actuators. In the case of MR PTER, the actuation can produceforce in three discrete directions.

Assuming that the direction of⇀

fh and the direction of the endpoint velocity are completely arbitraryat any point in the workspace, it is possible to compute the average of the difference between the

5

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e2

e1

e3

enen

θ1−2

θ2−3

θ3−...

θn

(a) The three lines of brakeforce at a specific configura-tion

e2

e1

e3

v

producible forces

(b) The brake forces at a spe-cific configuration with a spe-cific velocity

θf

θ3θ1 θ2

(c) The angles used to calculate brake actu-ation in blended control

Figure 3: Variables used for control calculations

direction of the commanded force⇀

fh and the direction of the actuated force. This will be referred to asthe average ”angle error” from now on. Since both velocity and haptic force direction are consideredrandom variables in the sense that they can be in any direction, the average angle error is actually anaverage over both variables.

At a given point in the workspace, each brake of an n-brake device produces a force along a line,and these force lines divide the workspace into 2*n regions as shown in Fig. 3(b). The regions aresymmetric about a line between the line of force labeled en and e1, so the analysis will look at n regions.The average angle error can be calculated by multiplying the probability that the velocity lies within acertain region by the average angle error within the region and summing over all regions. Equation 1shows this relationship somewhat explicitly in a form reminiscent of an entropy function from informationtheory or a variance function from statistics.

Avg (θerror) =∑

P (region) ∗ (AverageV alue) (1)

Since the velocity direction is assumed to be arbitrary, the probability of operating within a certainregion equals the size of the region divided by π:

P (region) =RegionSize

π(2)

The direction of velocity defines which region of Figs. 3(a) and 3(b) in which the control operates.More explicitly, the line perpendicular to the velocity defines the region because forces can only begenerated that are greater than π

2 radians away from the velocity. Figure 3(b) shows a specific velocityand position within the workspace of MR PTER, and the dotted line defines the region of producibleforces. Figure 3(c) shows the angular error as the commanded force ranges over all possible valuesfor the configuration in Fig. 3(b). The average angle error can be understood graphically by dividing thearea under the line in Fig. 3(c) by the range (in this case π), essentially integrating the error over allpossible values of θf and dividing by the range.

The velocity direction must also range over the full extent of the region. This motion is shown inFig. 4(a) as the velocity moves through the range of the region (as the perpendicular to the velocitymoves between e2 & e3. In doing so, the bracketed part of the graph shown in Fig. 4(b) shifts in thedirection of the arrow as the velocity direction shifts.

Using MR PTER, the average angle error for each region can be evaluated yielding Eqn. 3:

Avg (θerror) =2

(θ23 + (π − θ2)

2)

+((θ1 − θ3)

2 + (θ2 − theta1)2)

4π(3)

The average angle error at any point in the workspace can then be found by combining Eqns. 1, 2 & 3.This can then be plotted over the entire workspace of the device to provide a visualization of the ability

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e2

e1

e3

v

(a) Varying of the velocity direc-tion through a region

θf

θ3 θ1 θ2 π

θ err

or

(b) The angle error corresponding to vary-ing the velocity direction

θ1

θh

θ2

f2

fh

f1

(c) Variables used in multi-brake actuation

Figure 4: Variables and demonstration of the principle used in calculating the average angle error

Figure 5: The average angle error over the workspace using single brake actuation

of the device to produce an arbitrary force at a given point. Figure 5 shows a surface plot of Avg θerror

in the joint space of MR PTER.

4.1.2 Multi-Brake Actuation

A more complex actuation scheme involves simultaneously using multiple brakes. If the force to be

generated,⇀

fh, lies between two brake forces, they can be actuated in unison to produce an output force

that matches the direction of⇀

fh. In Fig. 2(c)⇀

fh2 would represent one such force. However if⇀

fh does

not lie between two brake forces as is the case with⇀

fh1 in Fig. 2(c) the nearest brake would be the onlypossible actuation

For calculation of this actuation scheme, the discussion uses the variables shown in Fig. 4(c). As-

sume⇀

fh lies between two brake forces, shown in this figure as⇀

f1 and⇀

f2. These forces are the resultantof a unit actuation of a brake, and are therefore a function of both endpoint velocity and kinematics and

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are calculated similar to Eqn. 4. Since there are more brakes and therefore more input torques than de-grees of freedom, the Jacobian of the system is non-square. To calculate the endpoint forces, a square(2x2) sub-matrix of the Jacobian is used that corresponds to the two input torques as in Eqn. 4. In thisequation, the subscripts of the Jacobian components represent the relationship between the cartesianand joint space variables. A similar equation can be derived to relate the torques at joints C & E to thecartesian forces.

[fx fy

]T =[

τA τB

]T ∗[

JAx JBx

JAy JBy

]−1

(4)

The force generated by a unit brake actuation can be found by sequentially setting each brake torqueto a unit strength and the other three torques to zero, then calculating the endpoint force. In this case,

the angle of the two brake forces on either side of⇀

fh is denoted by θ1 or θ2. The variable⇀

f1 denotes the

force generated by a unit torque of joint 1, and⇀

f2 is the result of a unit torque of joint 2. The variable

θh defines the direction of⇀

fh. The brakes are actuated so that the resultant endpoint force matches the

direction of⇀

fh. To assure this, the tangent of the linear combination of⇀

f1 and⇀

f2 in Eqn. 5 must match

the tangent of⇀

fh. This yields Eqn. 6

foutput = a ∗ f1 + b ∗ f2 (5)

sin(θh)cos(θh)

=a ∗ f1 ∗ sin(θ1) + b ∗ f2 ∗ sin(θ2)a ∗ f1 ∗ cos(θ1) + b ∗ f2 ∗ cos(θ2)

(6)

Solving for a and b yields Eqns. 7 & 8.

a =cos(θh) ∗ sin(θ2)− sin(θh) ∗ cos(θ2)

f1∗(cos(θ1) ∗ sin(θ2)− sin(θ1) ∗ cos(θ2))(7)

b =sin(θh) ∗ cos(θ1)− cos(θh) ∗ sin(θ1)

f2 ∗ (cos(θ1) ∗ sin(θ2)− sin(θ1) ∗ cos(θ2))(8)

The output force will match the direction of⇀

fh, if the ratio of brake actuation, defined as variables V1

& V2, matches the ratio of a to b. All of this can be normalized to match the magnitude of the commanded

force,⇀

fh bounded only by the maximum output of the actuators.

a

b=

V1

V2(9)√

V 21 + V 2

2 = |fh| (10)

The following brake actuation would result:

V1 =a ∗ |fh|√a2 + b2

(11)

V2 =b ∗ |fh|√a2 + b2

(12)

Similar to the discussion of angle error with the single-brake actuation, an average angle error canbe found throughout the workspace with this multi-brake actuation as well. In this case, if the desiredoutput force lies between two brake forces, the theoretical θerror goes to zero. Note that this analysisassumes a quasi-static case since the dynamics are currently ignored. Figure 6(a) depicts this rela-tionship graphically. Therefore through the same region of Fig. 4(a) that was used in looking at thesingle-brake actuation, the average angle error is defined by Eqn. 13. Throughout the workspace, this

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θf

θ3θ1 θ2

(a) Angle error at a specific point in the workspacefor a specific endpoint velocity

(b) The average angle error using multi-brake actuation

Figure 6: Angle error graphs for multi-brake actuation

value is graphed in Fig. 6(b). Note that the maximum values are the same for the two actuation schemesfor θA = θB ; however, when the two are not equal, Avg θerror decreases with multi-brake actuation.

Avg (θerror) =

(θ23 + (π − θ2)

2)

π(13)

4.1.3 Discussion

The idea of matching force direction follows in line with the previous research done by Gao [31]; howeverhis path-following theories do not directly apply to teleoperation. The idea of matching the direction ofan arbitrary force is far more important in a sense than the ability to steer to the left or right. However,the magnitude of the output force also plays a central role in the ability to reproduce forces. The pro-ceeding definitions and discussion have neglected this portion of the passive device’s force generationcapabilities due to the fact that it has not been fully explored yet.

Assuming that the passive actuators have a maximum torque, τmax. and again using the Jacobiandefined in Eqn. 4, by sequentially setting one joint torque to τmax and the others to zero, maximumendpoint forces can be found across the workspace. As the manipulator approaches singularities, theseforces increase toward infinity, however Figures 7(a) & 7(b) show the values of fmax over the jointspacefor maximal actuation of brakes A, B & C respectively.

These two metrics, θerror & Fmax have been chosen for early analysis; however they by no meansrepresent the ideal metrics to judge a device. They provide a very physical starting point from whichanalysis can build. The first step will be to perform an averaging analysis of Fmax similar to that done infinding the average angular error. Still these metrics make little sense without some grasp of the psycho-physical understanding of the human-device interface. Further metrics will then need to be developedwith the interface in mind.

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(a) Forces due to unit actuation of brake A or B (b) Forces due to unit actuation of brake E

Figure 7: Endpoint forces over the workspace caused by unit actuation of each the three individual brakes

Figure 8: Endpoint forces over the workspace caused by unit actuation of the three individual brakesand a photo of the overall teleoperation system

4.2 Force Calculation

Traditionally in a simple teleoperation scheme, the force displayed to the user is proportional to thedifference in position between the endpoint of the master and the slave. In this scheme, the slavefollows the master, and the human interacting with the master feels as if a virtual spring connects themaster to the slave. In such a scheme, Eqn. 14 defines K as the virtual spring constant that sets

the strength of the haptic coupling. Equation 15 represents the haptic force⇀

fh as a magnitude in thedirection of the unit vector

⇀eh.

fh= K ∗ (ps − pm) (14)⇀

fh= K ∗ |ps − pm|⇀eh (15)

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5 Preliminary Experiments

5.1 Master Hardware

Figure 1 illustrates the two degree of freedom (DOF) 4-link manipulator developed in previous researchby Reed & Book [39] [40] that is used as the haptic master to test the control algorithm. The two basejoints, A & B as well as joint E are actuated using LORD magneto-rheological brakes. The base angles,θA and θB in Fig. 1, are measured using encoders. The human user contacts the haptic master using ahandle that is attached to an ATI force sensor at joint D.

5.2 Slave Hardware

The research proposed here attempts to be slave-independent. The result of the research should andwill be applicable to nearly any device. Therefore discusion of the details of the slave is relativelyunimportant. The overall system is shown in the photograph in Fig. 8

As a side note, the current research using a 1-Dimensional slave began as a stepping stone insetting up a teleoperation system, the plan being to move to a 2-D slave device. However, constrainingthe master to the 1-D workspace of the slave device produces interesting control difficulties that mirrorprevious path-following research of Swanson [38] and Reed [39] [40].

5.3 Software

Both the master and slave devices are controlled using National Instruments LabVIEW software andrunning on NI control hardware. This graphical-based programming language allows for a priority basedmulti-threaded program structure, a screen shot of which is shown in Fig. 9(a). The newest versionof LabVIEW (not yet in use) also includes a specific variable classification for network-based commu-nication. Final versions of the control software will implement this network-variable under LabVIEWReal-Time to produce deterministic control.

5.4 Initial Testbed

A testbed has been designed to produce a repeatable environment over which the control schemescan be evaluated [53]. A constant force input (under quasi-static conditions) is created using a massattached to the handle of the master via a string. The testing compares the On-Off actuation, themulti-brake actuation with three K values (all using the simple virtual spring coupling), as well as anuncontrolled case. For each of the five controls, the test is run starting in 2 different positions. Eachstarting position test is run for three directions of input force. Figure 9(b) illustrates the workspaces ofthe master and the slave as well as the starting positions and force directions. The test is ended eitherwhen the master stops moving (the brake forces balance the input force) or when the master reachesthe virtual constraint at 60% of the slave’s workspace.

The results of this testing setup can be found in Table 1 and summarize the angular error as well asthe position error between the master and the slave. Lower angle error and lower position error can betaken to denote a better control.

5.5 CRS Robot Testbed

A constant force input, while quite repeatable, does a poor job of simulating human input. The decisionwas made to use a 6-DOF CRS robot to better simulate the input of a human operator.

With the help of a lab assistant, Carwyn Jones, a simple flexible coupling has been developed toconnect the CRS robot to MR PTER. The CRS robot was then programmed to follow a sinusoidal pathbetween two points symmetric about the workspace of the linear motor. The interface can be compared

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(a) Screenshot of the master control software

Master Workspace

Slave Workspace

Virtual Constraintpm1

pm2

fa1,2,3

fa1,2,3

(b) A line drawing of the master-slave system

Figure 9: The master-slave system in photographic, screenshot and line drawing form

Table 1: Results from constant force test

Control Position Difference Angle Error Time to Finish Trials UnfinishedNo Control 21.54% N/A 1.53 sec 0

On-Off Control 3.32% 0.68 rad 11.46 sec 0Blend K=10 19.67% 0.53 rad 1.67 sec 0

Blend K=100 6.84% 0.54 rad 7.34 sec 0Blend K=500 1.80% 0.48 rad N/A sec 18

Table 2: Position error from the CRS robot test (%of workspace)

No Control On-Off Multi K=10 K=100 K=500 AverageFlex 1 5.00 2.93 4.05 3.09 3.05 3.62

Input CRS Flex 2 5.15 3.34 2.68 3.59 3.19 3.59Robot Flex 3 5.19 3.47 4.48 4.15 3.25 4.18

connection Flex 4 5.00 4.14 4.76 4.54 4.66 4.62Rigid 5.03 4.80 4.28 4.98 4.76 4.77

Human 4.67 4.15 3.40 3.12 3.16 3.72

to simple models of the human operator as well as simple results of tests run with lab members. Fig-ure 10(a) shows the path of the endpoint of MR PTER when rigidly connected to the CRS ROBOT withno brake actuation. Figure 10(b) shows the path of the endpoint of MR PTER when controlled usinga simple virtual coupling between master and slave and a physical flexible coupling to the CRS robottraveling in the same path as before. The results provide a crude demonstration of the results that mightbe gained from human testing. Table 2 gives a summary of the list of average position error values usingthe CRS robot to drive MR PTER, and the bold values represent the trials shown in Figs. 10(a) & 10(b).

Position difference, while only one important component of the behavior of the haptic master control,provides a decent metric to compare the flexible coupling testbed to human input. Even though it showsroom for improvement, it highlights the ability of the simple virtual coupling based multi-brake control in

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(a) CRS Test: rigid connection (b) CRS Test: moderately flexible connection

Figure 10: Results of the experiment using the CRS robot to drive MR PTER

providing feedback.In both experiments, the control scheme shuts off as the position of haptic device approaches the

position of the slave (when the direction of the master’s velocity is in the direction of the position error).The control then resumes when the master device crosses the position of the slave device; however,since the master has gained energy while the control was off, that energy has to be dissipated before thedevice can be brought back to the position of the slave. This overshoot is somewhat visible in Fig. 10(b)and will be addressed in the next section.

6 Proposed Work

6.1 Advanced Force Calculation

To begin the extension of the research completed thus far, the algorithm for force generation will betotally re-thought. Possibly the most notable failing of a passive device centers around its inabilityto compensate for its own dynamics or internal forces. Typically, the behavior of a haptic device inteleoperation (or even in interaction with a virtual environment) can be judged by its transparency in thatbetter devices appear to be transparent to the user. The human interacting with the device should notfeel the dynamics or flaws of the master device but only feel the haptic forces that are intended to aid incompletion of whatever task is at hand. In an active the dynamics of the system can be modeled and themotors can compensate for them quite effectively. Since a passive device cannot arbitrarily generateforces, it similarly cannot arbitrarily compensate for its own dynamics.

Keeping that in mind, the proposed advanced force calculation scheme must take those factors into

effect. In addition to adding virtual damping to the coupling, components are added to the⇀

fh to use the

dynamics as part of the displayed force. If the dynamic force can be rolled into⇀

fh dynamic forces in

calculating⇀

fh, the user does not feel extra dynamic forces. The final form of⇀

fh will be broken into theparts shown in Eqn. 16.

fh=⇀

fdynamic +⇀

fcoupling (16)

The dynamics of the device are found using a constrained Lagrange approach using five state vari-ables q = [x, y, θA, θB , θE ]T and three constraint equations so that the five inputs can be easily usedas generalized inputs. The current form of the equations of motion can be seen in Eqn. 17 where Mrepresents a mass matrix, a represents the Jacobian constraint matrix, and the vector λ represents the

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Lagrange multipliers. These equations include no damping and only constant joint friction and will beexpanded in the future. [

M −aT

a [0]

] [qλ

]=

[Qaq

](17)

The coupling term of the calculation of fh will also be extended from the current spring coupling, thedetails of which still remain open to discussion and more thought.

6.2 Extension of Hardware and Software

In addition to improving the algorithms involved control, the hardware and software of the system willneed to undergo a change. While interesting limitations exist when using a 2-D device to control a 1-Ddevice, most teleoperation tasks utilize a slave device having the same DOF as the master device. Inverifying and testing the control algorithms, the research will extend to a 2-DOF slave device.

The software used to control the devices will similarly need an upgrade. Currently control of themaster device can be achieved no faster than 40Hz. While rates upward of 1kHz are required to beperceived as smooth [1], 500Hz would be acceptable and can likely be achieved by deploying themaster control using LabVIEW Real-Time.

6.3 Plan For Proceeding

The current literature review, preceding analysis, and previous work provide a basis for understandingthe nature of the problem at hand. The end goals of the research provide an idea of where the workis headed. All of this begs the question of how the research will progresses from the current state tocompletion in the next year and a half.

Immediate goals include an entire upgrade of the hardware and software used to test the developedtheories as well as to provide demonstrations. Work has already begun to extend the system to use a 2-DOF slave device so that the experiments can better represent teleoperation tasks. Rewriting the controlsoftware to optimize the communication and to run in Real-Time will also yield faster performance andsubsequently more transparent operation.

Aside from hardware upgrades, more work needs to be done to understand the human-machineinteraction of the haptic system before a useful haptic force generation algorithm can be developed.Work thus far has focused on kinematics as a method of judging a haptic device’s ability to performeffective feedback. Realistically the kinematics are an important component but only make up a part ofthe answer. Further background research will be required to identify the additional factors that contributeto a useful haptic interaction.

An intermediate step in this will be an experiment using the passive device to simulate a virtualspring. A passive device can produce a force proportional to a displacement as long as the user con-tinues to apply an input force. The forces felt by interacting with the virtual spring will be compared toan actual spring attached to the device in an attempt to look at a human user’s ability to distinguish be-tween different forces, essentially providing a test of the human user’s force fidelity on a passive device.While this experiment will not involve teleoperation, it will begin to lay the groundwork for understandingthe human user’s response to virtual forces. The results of this intermediate experiment combined withfurther human computer interaction literature review will allow the development of a fuller picture of how⇀

fh should be calculated.Further work must also be done developing the actuation algorithm. At any point in the workspace,

it is possible for a single brake’s angular velocity to go to zero while the endpoint continues to move. Inthat configuration, the forces produced by the brake at that joint will be perpendicular to the endpointvelocity, and their direction will be determined by the direction of the user input force. This createssomething of a singularity. Actuation of the stopped joint will sometimes produce no endpoint force. Theeffects of this singularity as well as how to control the device around these velocity singularities needsto be explored through analysis and testing.

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An understanding of these issues as well as the many unforeseen issues yet to develop will leadto the production of multiple algorithms for control and actuation. These algorithms will then be testedusing the hardware discussed previously in an attempt to provide meaningful results about the use of apassive haptic master during teleoperation.

7 Contributions

On some level, anything accomplished with the research proposed here will contribute new work to thefield of passive haptics. As evidenced by the short list of passive haptic devices in the passive hapticsection of the literature review, little research exists in the field. At this point, no research exists on usinga controllable passive haptic device in teleoperation (technically a joystick with a spring return can beconsidered a passive haptic device, but it is not controllable in a real-time sense). More specifically, theresearch presented here will have deliverables in two distinct sections that are familiar by now, forcegeneration and force calculation.

The research here will provide a theoretical framework for quantifiably discussing the ability of apassive device to act as a master in teleoperation. The entropy function used to calculate the averageangular error and developed here can easily be extended to a planar manipulator with n brakes. Sim-ilarly, the force generation analysis developed briefly here and to be extended in the future researchwill address the strength of a brake-actuated passive manipulator. These two metrics combined withthe human-computer interaction metrics provide a basis for judging the ability of a device to recreate avector force to be used as haptic feedback in teleoperation.

As part of this, a the 6-DOF CRS robot will be used to test the actual ability of MR PTER to produceforces. An experiment will be designed to validate the theoretical metrics as applied to MR PTER.Without this validation, further development of a haptic force calculation scheme makes little sense.

The second portion of the proposed contributions focuses on the force calculation in a passivehaptic teleopoerator. The intermediate results with a linear slave device show the drawbacks of thesimple virtual coupling (a contribution in and of itself). With those drawbacks in mind, the proposedresearch will further develop a force calculation scheme that will provide usable haptic feedback duringteleoperation. In reality, the difficulty in judging a human-computer interface hinges upon the word”usable.” The job of a haptic device is not necessarily to reproduce a force exactly but instead to providehelpful feedback to a human user that assists in completion of a task.

To be able to judge the ability of a control scheme to produce ”usable” feedback, relatively extensivehuman testing must be completed. Details of the experimental design are far from solidified. However,the experiment will be a realistic teleoperation task. Realistically, it would be interesting to design a taskto simulate haptically enhanced remote surgery such as the research by Rossi & Boschetti [51][52]. Apassive master provides the perfect platform for surgery assistance due to the fact that the system isentirely driven by the human operator. While active haptic surgery assistive devices share some controlwith the surgeon, a passive device could only slow down or guide the surgeon’s hand.

The total contribution of the research presented here will be a combination of everything discussedthus far. The end product of of the research will include theoretical discussion of passive haptic devicesin addition to the application and testing of the theories.

8 Acknowledgments

The research presented here gains most of its support (financial, hardware and software) from NationalInstruments and their division of Academic Relations. I would especially like to thank Jeannie Falcon,and Morten Jensen for their interest in the project. It is also important to thank the IMDL and the FPMCfor their support. Most importantly, I would like to thank my significant other (my girlfriend, my fiance,and my wife through the process), Amanda.

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