CRC Press - Robotics and Automation Handbook Episode 2 Part 9 pptx

Robotics in Medical Applications 25
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25.6.3 Invasive Robotic Surgery ROBODOC
®
Surgical Assistant
As a final example in this chapter, we will look at the ROBODOC Surgical Assistant offered by Integrated
Surgical Systems of Davis, California. The ROBODOC system is used currently for proceduresthattypically
tendtobefullyinvasive type of surgical procedures—total hip replacement and total knee replacement.The
system is designed to aid doctors with hip implants and other bone implants, through more accurate fitting
and positioning. The advantage currently offered by ROBODOC system is accuracy, which should translate
into better patient outcomes. According to Integrated Surgical Systems’ own literature, a typical surgical
procedure without robotic assistance will routinely leave a gap of1 mm or greater between the boneand the
implant. ROBODOC aidsthe surgeon in shaping thepatient’s bone to match the implant to within 0.5mm.
The ROBODOC system incorporates a computer planning system combined with a five-axis robot
(see Figure 25.6). The robot carries a high-speed end-milling device to do the shaping. One should note
the theme of preplanning, which is pervasive in robotic surgery — given adequate information prior to
the procedure (CT scans, MR scans, PET scans); a good planning component exploits the precision and
degrees of freedom of a robot to offer a better technical option for the procedure.
Follow-up studies on ROBODOC cases support the fundamental thesis of robots in medicine of en-
hanced outcomes: better fit and positioning of the implant to the bone (based on x-ray evaluations) with
fewer fractures, as one might expect based on better fit and more accurate positioning. With development
of newer technology, the ROBODOC system offers the potential for performing the surgery through a very
small incision [Sahay et al. 2004] of about 3 cm compared to standard incision sizes of about 15 cm. Thus,
even in the area of joint surgery that is typically an invasive procedure, robotic systems offer the potential
for reducing invasiveness while maintaining the advantage of precision and accuracy.
FIGURE 25.6 ROBODOC Surgical Assistant System for hip replacement. (Source: Integrated Surgical Systems)
Copyright © 2005 by CRC Press LLC
25
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FIGURE 25.7 Artist’s rendering of robotic hair transplantation system. (Source: Restoration Robotics, Inc.)
25.6.4 Upcoming Products

Robotics in medicine has been on the rise. There will be newer products that employ robots in various
different practices of medicine. Two such new products that are in development are described here.
1. HairTransplantationRobot: A roboticsystemusingimageguidance is being developedtoperform
hair transplants. Hair transplantation is a successful procedure that is performed routinely across
the world. The procedure involves transplanting 1000 to 2000 individual follicular units from a
donor area of the patient (back of the head) to the target area of the patient (bald spot or thinning
area on the head). The procedure is highly tedious, repetitive, and prone to errors due to fatigue
in the surgeon as well as the technicians. A robotic system that automates this process is being
developed by Restoration Robotics, Inc., Sunnyvale, California, which will eliminate the tedium,
thus enhancing the quality of the transplants (Figure 25.7).
2. Robotic Catheter System: A telerobotic device is being developed to guide catheters in patients.
Cardiac surgery has undergone drastic changes in the past decade. There are fewer and fewer open
heart surgeries being performed and most of the problems related to the heart are being addressed
by delivering the appropriate treatment using catheters. These procedures have become routine
in most of the hospitals. However, guiding the catheter through the patient involves tedious work
for the surgeon. Furthermore, in order for the physician to observe the position of the catheter,
the patient needs to be monitored using x-rays, which also exposes the surgeon while he or she
is guiding the catheter. Hansen Medical, Palo Alto, California, is developing a robotic catheter
system with broad capabilities as a standalone instrument or highly-controllable guide catheter to
manipulate other minimally invasive instruments via a working lumen formed by the device. The
system has very sophisticated control and visualization aspects to enable an operator to navigate
and conduct procedures remotely with high degrees of precision. This system removes the tedium
in the procedure as well as enables the surgeon to stay out of the radiation field of the x-ray machine.
Bibliography
Adler, J.R., Frameless radiosurgery, in: Goetsch, S.J. and DeSalles, A.A.F. (eds.), Sterotactic Surgery and
Radiosurgery, Medical Physics Publishing, Wisconsin, vol. 17, pp. 237–248, 1993.
Adler, J.R., Murphy, M.J., Chang, S.D., and Hancock, S.L., Image-guided robotic radiosurgery, Neuro-
surgery, 44(6):1299–1307, June 1999.
Copyright © 2005 by CRC Press LLC
Robotics in Medical Applications 25

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Bodduluri, M. and McCarthy, J.M. X-ray guided robotic radiosurgery for solid tumors, Indus. Robot J.,
29:3, March 2002.
Carts-Powell, Y., Robotics transforming the operating room, OE Reports (SPIE), 201, September 2000.
Chenery, S.G., Chehabi, H.H., Davis, D.M., and Adler, J.R., The CyberKnife: beta system description and
initial clinical results, J. Radiosurg., 1(4):241–249, 1998.
Larsson, B., Leksell, L., and Rexed, B., The high energy proton beam as a neurosurgical tool, Nature,
182:1222–1223, 1958.
Leksell, L., The stereotaxic method and radiosurgery of the brain, Acta Chir. Scand., 102:316–319, 1951.
Murphy, M.J. and Cox, R.S., The accuracy of dose localization for an image-guided frameless radiosugery
system, Med. Phys., 23(12):2043–2049, 1996.
Murphy, M.J., Adler, J.R., Bodduluri, M., Dooley, J., Forster, K., Hai, J., Le, Q., Luxton, G., Martin, D., and
Poen, J., Image-guided radiosurgery for the spine and pancreas, Comput. Aided Surg., 5:278–288,
2000.
Sahay, A., Witherspoon, L., and Bargar, W.L., Computer model-based study for minimally invasive THR
femoral cavity preparation using the ROBODOC system, Proceedings of the Computer-Aided Ortho-
pedic Surgery Meeting, Chicago, IL, June 2004.
Schweikard, A., Adler, J.R., and Latombe, J.C., Motion planning in stereotaxic radiosurgery, Proceedings of
the International Conference on Robotics and Automation, vol. 9, pp. 1909–1916, IEEE Press, 1993.
Schweikard, A., Tombropoulos, R.Z., Adler, J.R., and Latombe, J.C., Treatment planning for a radiosur-
gical system with general kinematics, Proceedings of the International Conference on Robotics and
Automation, vol. 10, pp. 1720–1727, IEEE Press, 1994.
Sugano, N. and Ochi, T., Medical robotics and computer-assisted surgery in the surgical treatment of
patients with rheumatic diseases, www.rheuma21st.com, published April 27, 2000.
Tatter, S.B., History of stereotactic radiosurgery, MGH
Neurological Service, 1998.
World Robotics 2003, United Nations Economic Commission for Europe, October 2003.
Copyright © 2005 by CRC Press LLC
26
Manufacturing

Automation
Hodge Jenkins
Mercer University
26.1 Introduction
26.2 Process Questions for Control
26.3 Terminology
26.4 Hierarchy of Control and Automation
History
26.5 Controllers
PLC: Programmable Logic Controller
•
DCS: Distributed
Control System
•
Hybrid Controller
•
Motion Controller
•
PC-Based Open Controller
26.6 Control Elements
HMI: Human-Machine Interface
•
I/O: Inputs and Outputs
26.7 Networking and Interfacing
Sensor-Level I/O Protocol
•
Device-Level Networks
•
Advanced Process Control Fieldbuses
•

Controller
Networks
•
Information Networks and Ethernet
•
Selection
of Controllers and Networks
26.8 Programming
Ladder Logic Diagrams
•
Structured Text
•
Function Block
Diagram
•
Sequential Flow Chart
•
IL: Instruction List
•
Selection of Languages
26.9 Industrial Case Study
26.10 Conclusion
26.1 Introduction
As the global marketplace demands higher quality goods and lower costs, factory floor automation has
been changing from separate machines with simple hardware-based controls, if any, to an integrated
manufacturing enterprise with linked and sophisticated control and data systems. For many organizations
the transformation has been gradual, starting with the introduction of programmable logic controllers
and personal computers to machines and processes. However, for others the change has been rapid and
is still accelerating. This chapter discusses the current state of control and data systems that make up
manufacturing automation.

26.2 Process Questions for Control
The appropriate level of control and automation depends on the process to be automated. Before this can
be accomplished, questions about the physical process and product requirements must be answered.
Copyright © 2005 by CRC Press LLC
Manufacturing Automation 26
-3
Advanced Loop Control
PID Loop Control
Event Control Motion Control
Enterprise Automation
Quality Control & SPC
Process Control
Multi-Process Control
FIGURE 26.1 Hierarchy of automation and control.
relativelysimplecontrolmethods.Eventcontrolwasoftenaccomplishedwithrelaylogic.Automaticcontrol
was all hardware-based, and as such it was not easily changed or improved.
As microprocessors became more prevalent and accepted in the later part of the 20th century, pro-
grammable logic controllers (PLC) were introduced and vastly improved process event control and pro-
vided the ability to easily modify a process. A separate and parallel action was programmable motion
controllers. With the increasing computational power of successive versions of microprocessors, propor-
tional, integral, and derivative (PID) control was easily implemented in these controllers. This allowed
relatively easy tuning of servomechanisms. Communication between the two controller types was initially
analog signals, then serial data, and most recently one of several data networks. While the first motion and
process controllers were great milestones, integrated process and motion control with real-time process
data availability didnot appear untilthe late 1990s. Critical processes, such as high speed drawing of optical
fiber, required tightly couple motion and process control to manufacture competitively.
Thus, modern manufacturing automation systems joined motion control and process control together
for greater flexibility and controlpotential. Along with this improvement came newer andfaster data buses,
Production
Database

(SQL Server)
Production
server
Web-Based Production
Report
Data Collection
Connection
Interactive Data
Query, VB
Applications
Financial Reporting
SPC
Feedback
PLC/HMI Control System
FIGURE 26.2 Manufacturing management information flow.
Copyright © 2005 by CRC Press LLC
Manufacturing Automation 26
-7
SHUTDOWNSECURITY LOCKOUT INITIALIZE MANUAL AUTO STOP
Pyrometer
Flame Detectors
deg. C Laser Intens.
SPINDLE TRAVERSE
To p
LIMITs
Home
mm/hr
mm/sec.
mm.
mm.

mm.
mm.
min. sec
Run Count
Recipe Status Info
Recipe Name:
Preform ID:
Speed:
Clad Torch Box Temp
deg. C
deg. C
Core Torch Box Temp
Position:
Speed:
Position:
End Burner
Outside Torch
Inside Torch
Current User:
Time in sequence
Time in Step
Phase
Step #
Gas Mode #
Chm. Mode #
min. sec
Requested
Traverse Pass #
Set length
Current Length

Home Position
deg/sec
deg.
Complete
Calculator
mm/hr
Averaging window
Avg. Traverse Speed
Bottom
LASER
ENABLE
Main Bulk Gas
Chemical
Delivery
Bubbler
Systems
Sequence
&
Transitions
Motion Trends
PIDs
Support
Systems
Current Traverse Speed
FIGURE 26.4 HMI main menu example.
Bulk Gas System #1
CC06 GAS
AV17
TO BGS 2
SOLENOID VALVES

MV01
MV02
MFC01 MFC13
MFC14
MFC10
MFC11
MFC03
MFC06
MFC07
slpm
slpm
slpm
slpm
slpm
Inside
Inside
Outside
Outside
Endbumer
slpm
slpm
slpm
Inside
Inside
Inside
Outside
Outside
Inside
Endbumer
slpm

slpm
slpm
slpm
MFC02
MFC04
MFC05
MFC08
MV103
MV101
MV03
MV04
O2 Main
H2 Main
O2
AR
H2
AV01
AV05
AV06
AV09
AV10
AV15
AV03
AV08
AV12
AV14
AV16
AV07
AV11
AV13

AV04
AV02
FIGURE 26.5 HMI gas delivery sub-system menu example.
Copyright © 2005 by CRC Press LLC
Manufacturing Automation 26
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References
[1] Bob Waterbury, DCS, PLC, PC, or PAS?, Control Eng., p. 12, July 2001.
[2] Geller, D.A., Programmable Controllers using the Allen-Bradley SLC-500 Family, Prentice Hall, Upper
Saddle River, NJ, 2000.
[3] Piyevsky, S., Open network and automation products, Allen-Bradley Automation Fair, Anaheim, CA,
21 November 2002.
[4] Fielder, P.J. and Schlib, C.J., Open architecture systems for robotic workcell integration, IWACT
1997 Conference Proceedings, Columbia, OH, 1997.
[5] Soft PLC Overview, URL: />[6] Mintchell, G.A., HMI/SCADA software-more than pretty pictures, Control Eng., 49, 18, December
2002.
[7] OPTO22 Factory Floor Software, v 3.1,D, OPTODisplay User Guide, Form 723-010216, OPTO22,
2001.
[8] Meldrum, N., ControlLogix
®
and HART protocol an integrated solution, Spectrum Controls, 2002.
[9] Fieldbuses, look before you leap, EDN, p. 197, 1998.
[10] URL: , 2003.
[11] Open DeviceNet Vendor Association (ODVA), URL: , 2003.
[12] Profibus International, URL: fibus.org, 2003.
[13] IEC 61158, Digital data communications for measurement and control — Fieldbus for use in in-
dustrial control systems — Part 1: Overview and guidance, IEC, Geneva, 2003.
[14] ControlNet International, URL: , 2003.
[15] Foundation fieldbus, http://www.fieldbus.org, 2003.
[16] Lee, K.C. and Lee, S., “Performance evaluation of switched Ethernet for real-time industrial com-

munications,” Computer Standards Interfaces, vol. 24, no. 5, pp. 411–423, November 2002.
[17] IEC 61131-3, Programmable controllers — Part 3: Programming languages, IEC, Geneva, 2003.
[18] IEC 61508-1, Functional safety of electrical/electronic/programmable electronic safety-related sys-
tems — Part 1, IEC, Geneva, 1998.
[19] ANSI/ISA-S84.01-1996, Application of safety instrumented systems for the process industries, In-
strument Society of America S84.01 Standard, Research Triangle Park, NC 27709, February 1996.
Copyright © 2005 by CRC Press LLC
Index
A
A465, 11-4
AABB, 23-18
ABB, 1-8
Abb
´
e error (sine error), 13-5f
Abb
´
e principle, 13-4–5
Absolute coordinates
of vector x, 2-3
Absolute coordinate system, 20-3f
Absolute encoders, 12-3
example, 12-3f
Acceleration control for payload limits, 11-18
Accelerations, 4-9, 12-9–10
of center of mass, 4-6
online reconstruction of, 14-9–10
Acceptance procedures, 10-2
Accuracy, 13-3f
definition of, 13-2–3

AC&E’s CimStation Robotics, 21-7, 21-8
ACS, 24-36f, 24-37f
Active touch, 23-9, 23-11
Activity of force F, 6-4
Activity principle, 6-4
Actuator forces, 19-2f
Actuators, 12-12–18, 13-17
ADAMS
Kane’s method, 6-27
Adaptive command shaping (ACS), 24-36f, 24-37f
Adaptive feedback linearization, 17-16–18
Adjoint
Jacobian matrices, 2-12
Adjoint transformation, 5-3
Admittance regulation
vs. impedance, 19-9–10
Advanced feedback control schemes, 24-29–31
with observers, 24-30–31
obstacles and objectives, 24-29–30
passive controller design with tip position feedback,
24-31
sliding mode control, 24-31
strain and strain rate feedback, 24-31
Advanced process control fieldbuses, 26-11
Affine connection, 5-10
Affine projection, 22-4
AI, 1-5
AIBO, 1-11
AIC, 1-5
Aliasing, 13-9–10

frequency-domain view of, 13-10f
Alignment errors, 13-4–5
Al Qaeda, 1-10
Ambient temperature, 10-2
American Machine and Foundry, 1-7
AMF Corporation, 1-7
Analog displacement sensors, 12-4–5
Analog photoelectric, 12-7
Analog sensors, 12-4–10, 13-18–19
analog filtering, 13-19f
Analog-to-digital conversion, 13-11
Analyzing coupled systems, 19-8–9
Angular error motions, 10-6t, 10-9f
Angular velocity
and Jacobians associated with parametrized rotations,
2-8–10
ANSI Y14.5M, 10-3
Anticipatory control, 23-12–13
Approximations, 24-25
ARB IRB1400, 17-2f
Aristotle, 23-10
ARMA, 14-13
Arm controller
robot end effector integrated into, 11-4f
Arm degrees of freedom augmentation, 24-39–41
bracing strategies, 24-39
inertial damping, 24-40
piezoelectric actuation for damping, 24-41
Articulating fingers, 11-11
Artificial intelligence (AI), 1-5

Artificial Intelligence Center (AIC), 1-5
ASEA, Brown and Boveri (ABB), 1-8
ASEA Group, 1-8
Asimov, Isaac, 1-3–4, 1-4, 1-6
Asimov, Janet Jeppson, 1-4
Asimov, Stanley, 1-4
Assembly task
two parts by two arms, 20-10
Augmented dynamics-based control algorithm, 20-7, 20-7f
I-1
I-2 Robotics and Automation Handbook
Augmented reality, 23-3
AUTOLEEV
Kane’s method, 6-27
Automated system
forming leads on electronic packages, 10-13f
leads location, 10-14f
Automatic calculator invention, 1-2
Automatic rifle, 1-2
Automatic symmetry cell
detection, matching and reconstruction, 22-18–21
Automaton, 1-3
Autoregressive moving-average (ARMA), 14-13
Axis, 5-3
Axis-aligned bounding boxes (AABB), 23-18
6-axis robot manipulator with five revolute joints, 8-13
B
Babbage, Charles, 1-2
Backward recursion, 4-2
Ball races, 12-13

Bar elements
distributed, 24-15
Bares, John, 1-7
Bargar, William, 1-10
Bars and compression, 24-5
Base frame, 2-3, 17-3
Base parameter set (BPS), 14-5
batch LS estimation, 14-7–8
element estimation, 14-7–8
estimation, 14-19–21
online gradient estimator, 14-8
Batch LS estimation
of BPS, 14-7–8
BBN criteria, 13-15
Beam elements in bending
distributed, 24-15–16
Beams and bending, 24-6–7
Bending deformation
geometry of, 24-6f
Bending transfer matrix, 24-16f
Bernoulli-Euler beam model, 6-21
Bernoulli-Euler beam theory, 6-16
Bezout identity, 17-14
Bilateral or force-reflecting teleoperator, 23-2
Body, 5-3–4
Body-fixed coordinate frame, 5-1
Body manipulator Jacobian matrix, 5-5
Bolt Beranek & Newman (BBN) criteria, 13-15
Bond graph modeling, 4-2
BPS. See Base parameter set (BPS)

Bracing strategies
arm degrees of freedom augmentation, 24-39
Bridge crane example, 9-4–6
Broad phase, 23-18–19
Brooks, Rodney, 1-10
BrownBoveriLTD,1-8
Buckling, 24-7–9
Building
reconstruction, 22-21f
C
Cable-driven Hexaglide, 9-1
Cable management, 13-7
CAD and graphical visualization tools, 21-1
Cadmus, 1-1
Calibration cube
four images used to reconstruct, 22-12f
two images, 22-7f
two views, 22-7f
Camera calibration, 22-4
Camera model, 22-2–3
Camera poses
cell structure recovered, 22-21f
CAN, 26-10
Capacitive displacement sensors, 12-5–6
distance and area variation in, 12-6f
Capek, Jose, 1-3
Capek, Karel, 1-3
Carl Sagan Memorial Station, 1-9
Carnegie Mellon University, 1-7
Cartesian error, 15-22f

Cartesian manipulator
stiffness control of, 16-5–6
Cell structure recovered
camera poses, 22-21f
Centrifugal forces, 4-8
Centrifugal stiffening, 6-14
Characterizing human user
haptic interface to virtual environments, 23-5
Chasles’ Theorem, 2-5, 2-6, 5-3
Chatter free sliding control, 18-4–6
Chemical process control, 26-18f
Christoffel symbols, 5-8, 5-10
of first kind, 17-5
CimStation Robotics, 21-2
CimStation simulated floor, 21-2f
Cincinnati Milacron Corporation, 1-8
Closed-form equations, 4-7–8
Closed-form solutions
vs. recursive IK solutions, 14-18f
Closed kinematic chains, 24-10
Collision detection, 23-17, 23-18–19
Collision detector, 23-17
flowchart, 23-18f
Collision sensors, 11-17
Column buckling, 24-8
Combinations of loading, 24-7–9
Combined distributed effects and components, 24-16
Command generation, 9-4
Command shaping filter, 24-34
Common velocity

bond graph, 19-8f, 19-9f
feedback representation, 19-8f, 19-9f
Compensation based on system models, 23-15
Compliance based control algorithm, 20-6, 20-6f
Compliant support of object, 20-8f
Composition of motions, 2-5
Compressed air, 11-8
Compression
and bars, 24-5
Index I-3
Computational complexity reduction, 24-27
Computed torque, 17-8
Computed-torque control design, 15-5–6
Computejacobian.c, 3-18, 3-23–24
Conductive brushes, 12-15
Configuration, 5-2
infinite numbers
with none, 3-3f
with one, 3-3f
Configuration space, 17-3
Consolidated Controls Corporation, 1-5
Constrained Euler-Lagrange equation
geometric interpretation, 5-12
Constrained layer dampers, 13-15
Constrained systems, 5-11–13
Constraint(s), 13-6
Kane’s method, 6-14
Constraint connection, 5-12
Constraint distribution, 5-12
Constraint forces and torques

between interacting bodies, 7-15–16, 7-15f
Contents description, 24-2
Continuously elastic translating link, 6-17f
Continuous motion, 22-8
Continuous system
Kane’s method, 6-16
Control, 24-27
Control algorithms, 13-19–21
Control architecture, 17-7
Control bandwidth, 15-2
Control design, 16-5–6, 16-6–8, 16-12–14
with feedback linearization, 15-6–10
method taxonomy, 17-6–8
µ-synthesis feedback, 15-16–19
Control effort
tracking of various frequencies
with feedforward compensation, 9-20f
without feedforward compensation, 9-17
Controller(s)
experimental evaluation, 15-19–21
implementation, 13-16–17
networks, 26-11–12
selection of, 26-13
Controller area network (CAN), 26-10
ControlNet, 26-11, 26-12
Control system design, 17-8
Conventional controllers
bode plots of, 15-14f
Coordinated motion control
algorithm, 20-7–9

based on impedance control law, 20-7–10
of multiple manipulators
for handling an object, 20-5–7
problems of multiple manipulators, 20-5–7
Coordinate frames, 8-3, 8-13
schematic, 8-3
Coordinate measuring machine
deflection of, 9-3f
Coordinate systems, 20-3f
associated with link n, 4-3f
Coriolis centrifugal forces, 5-8
Coriolis effect, 4-7
Coriolis force, 4-8
Coriolis matrix, 5-8
Corless-Leitmann approach, 17-14
Correlation among multiple criteria, 10-13–14
Cosine error
example of, 13-4f
CosmosMotion, 21-10
cost, 21-10
Coupled stability, 19-10–13
Coupled system stability analysis, 19-10
Couples systems poles
locus of, 19-13f
Covariant derivative, 5-10
CPS
of tracking errors, 15-20
Craig notation and nomenclature, 3-3
Crane response to pressing move button, 9-5f
Crane response to pressing move button twice, 9-5f

Critical curve, 10-16
calculating points on, 10-18f
Critical surface, 22-8
Cross-over frequencies, 15-18t
Ctesibus of Alexandria, 1-2
Cube
reconstruction from single view, 22-17f
Cube drawing
example, 21-12
Cumulative power spectra (CPS)
of tracking errors, 15-20
Cutting tool, 10-16f
envelope surface, 10-16f
as surface of revolution, 10-17f
swept volume, 10-16f
CyberKnife stereotactic radiosurgery system, 25-6–9, 25-7f
accuracy and calibration, 25-9
computer software, 25-8–9
patient positioning, 25-8
patient safety, 25-9
radiation source, 25-7
robotic advantage, 25-9
robot manipulator, 25-7
stereo x-ray imaging system, 25-8
treatment planning system for, 25-8, 25-8f
D
DADS, 21-10
Damping, 24-4–5
inertial
arm degrees of freedom augmentation, 24-40

three axis arm as micromanipulator for, 24-41f
inertial controller
quenching flexible base oscillations, 24-41f
passive, 24-39, 24-40f
sectioned constraining layer, 24-39f
piezoelectric actuation for
arm degrees of freedom augmentation, 24-41
Dante, 1-7
Dante II, 1-7
DARPA, 1-6
I-4 Robotics and Automation Handbook
Dartmouth Summer Research Project on Artificial
Intelligence, 1-6
Da Vinci Surgical System, 1-11, 25-9–10, 25-10f
DC brushless motor, 12-16
DC brush motor, 12-15–16, 12-15f
Decentralized conventional feedback control, 15-3–5
Decentralized motion control
with PD feedback and acceleration feedforward, 15-4f
Decentralized PD, 15-2
controllers
control torques produced with, 14-23f
Defense Advanced Research Projects Agency (DARPA), 1-6
Deformable bodies mechanics, 24-2–3
DEMLIA’s IGRIP, 21-7
Denavit-Hartenberg (D-H), 8-1
approach, 3-4
convention, 8-1–21
examples, 8-8–21
frame assignment, 3-8

framework, 2-7
notation, 21-7
parameters, 3-11–13, 8-1–5
C-code, 3-18, 3-29–30
determining for Stanford arm, 8-13
example PUMA 560, 3-11t
flow chart, 8-5f–6f
schematic, 8-4f
systematic derivation, 8-4
pathology, 2-7
procedure, 3-4
representation, 21-14
transformation, 4-1
Density, 24-4
Desired object impedance, 20-8f
Detent torque, 12-14
Determinism, 13-4
Device-level networks, 26-10–11
DeviceNet, 26-10
Devol, George C., 1-4–5
Dexterity, 20-2f
D-H. See Denavit-Hartenberg (D-H)
Dh.dat, 3-18, 3-28
Different image surfaces, 22-4
Digital sensors, 12-10–12
common uses for, 12-11–12
with NPN open collector output, 12-11f
Digital-to-analog conversion, 13-13–14
Direct collision detection, 23-19
Direct-drive robotic manipulator modeling and

identification, 14-14–15
experimental setup, 14-14–15
Direct impedance modulation, 19-17–18
Discrete-time samples
multiple continuous time-frequencies, 13-10f
Discrete-time system
sampling and aliasing, 13-9–10
Discrete-time system fundamentals, 13-9–14
Discretization of spatial domain, 24-19–25
Disk and link interaction, 7-19–21, 7-20f
Dispensers, 11-16
Displacement vector, 8-3
Distributed bar elements, 24-15
Distributed beam elements in bending, 24-15–16
Distributed control system (DCS), 26-5
Distributed models, 24-15
Distributed shaft elements, 24-15
Disturbances
feedforward compensation of, 9-15f
DOF model, 21-17f
single
Matlab code, 21-23–24
DOF planar robot
grasping object, 6-15f
with one revolute joint an one prismatic joint, 6-8–13
with two revolute joints, 6-4–8
3-DOF system
full sea state
Matlab code, 21-24–27
Double integrator system, 17-8

Double pendulum in the plane, 7-16–18
associated interaction forces, 7-16f
Double pole single throw (DPST) switch, 12-10, 12-10f
Doubles two matrices
C-code, 3-28–29
DPST switch, 12-10, 12-10f
Drive related errors, 10-6t
Drone, 1-10
Duality principle, 16-10–12
Ductile materials static failure, 24-3
Dynamical scenes, 22-13
Dynamic data exchange (DDE), 26-6
Dynamic effects, 10-6t
Dynamic equation, 5-1, 5-6–11
of motion, 21-17
Dynamic models, 16-2–4
in closed form
and kinematics, 14-15–17
Dynamic Motion Simulation (DADS), 21-10
DYNAMICS, 6-3
Dynamics, 17-5, 24-11–15
error
block diagram, 17-9f
Dynamics solver
flowchart, 23-18f
E
Eddy current sensors, 12-5
Edinburgh Modular Arm System (EMAS), 1-11
Eigenfunctions, 24-18–19
Eigenvalues and corresponding eigenfunctions, 24-18–19

Eight-point linear algorithm, 22-4, 22-5
coplanar features, 22-7–8
homography, 22-7–8
Eight-point structure from motion algorithm, 22-6
Elastic averaging, 13-6
Elastic modulus, 24-3–4
Elbow manipulator, 3-5, 3-5f
link frame attachments, 3-5f
Electrical power, 11-9
Electromagnetic actuators, 12-12–17
Electromagnets, 11-16
Index I-5
Electronic leads
foot side overhang
specification, 10-4f
Electronic numerical integrator and computer (ENIAC),
1-5
EMAS, 1-11
Embedding of constraints
dynamic equations, 5-12
Encoders, 12-1, 13-11–12
typical design, 12-2f
Endeffector(s), 5-4
attachment precision, 11-4–5
design of, 11-1–19
grasping modes, forces, and stability, 11-11–13
gripper kinematics, 11-9–11
grippers and jaw design guidelines, 11-13–16
interchangeable, 11-16
multi-tool, 11-17f

power sources, 11-7–9
robot attachment and payload capacity, 11-3–7
sensors and control considerations, 11-17–19
special environments, 11-3
special locations, 11-5
Endeffector frame, 17-3
transformation to base frame, 8-8f
Endoscopic surgery, 1-10
Engelberger, Joseph F., 1-4–5, 1-10
Engelberger Robotics Awards, 1-5
ENIAC, 1-5
Environmental forces, 19-2f
Environmental impedances
types of, 16-10f
Environmental issues, 1-3
Environmental stiffness
locus of coupled system poles, 19-14f
Epipolar constraint, 22-4–5
Equations of motion
of rigid body, 7-13–14
Equivalent control, 18-4–6
Ergonomic simulation, 21-8f
Ernst, Heinrich A., 1-6
Error bounds
linear vs. quadratic, 17-13f
Error budgeting, 10-1–20
accuracy and process capability assessment,
10-12–15
error sources, 10-5–7, 10-6t
probability, 10-2–3

tolerances, 10-3–5
Error dynamics
block diagram, 17-9f
Error equation, 17-9
Error sources, 10-1
effects on roundness, 10-15f
superposition of, 10-15f
Essential matrix, 22-4–5, 22-6
Ethernet, 26-11, 26-12, 26-12f
Euclidean distance, 2-1
Euler angles, 2-4, 17-4
Euler-Lagrange equations, 5-6
Euler’s equation of motion, 4-3f
Euler’s equations
covariant derivative, 7-8–11
disadvantages of, 7-8
in group coordinates, 7-12
rigid body, 7-11–13
Exact-constraint, 13-6
Exciting trajectory
motions of, 14-20f
Exciting trajectory design, 14-8–9
Exploratory procedures, 23-10
Exponential coordinates, 5-3
Exponential map, 5-2
action on group, 7-9f
Extended forward kinematics map, 5-4
F
Factorization algorithm
multilinear constraints, 22-13

Factory floor, 21-3f
Fault tree analysis (FTA), 25-4
FBD, 26-15
Feasibility, 10-1
Feature extraction, 22-3
Feature matching, 22-3
Feature tracking, 22-3
Feedback compensation, 13-20
Feedback control design
µ-synthesis, 15-16–19
Feedback control hardware, 13-16
Feedback controller C1
bode plots of, 15-18f
Feedback linearization control, 17-7–8
Feedback sensors, 13-17–19
Feedforward compensation, 13-21
5% model errors effect on, 9-18f
10% model errors effect on, 9-19f
Feedforward control
action, 9-15–16
conversion to command shaping, 9-23–24
Feedforward controllers, 9-4
Fictitious constraints, 6-16
Fieldbuses
advanced process control, 26-11
capabilities, 26-13f
Filippov solutions, 17-15
Finite element representations, 24-25
First joint
flexible dynamics, 15-11f

sensitivity functions for, 15-16f
First U.S. robot patent, 1-5
Fixturing errors, 10-6t
FK, 14-2
map, 5-4, 17-3–4
Flexible arm
kinematics of, 24-20
Flexible exhaust hose, 21-3
Flexible robot arms, 24-1–42
design and operational strategies, 24-39–41
open and loop feedforward control
command filtering, 24-32–35
I-6 Robotics and Automation Handbook
Flexible robots trajectory planning, 9-1–25
applications, 9-13–14
Flight simulation, 23-2
Fluid power actuators, 12-17–18
Folded back, 3-2
Food processing, 11-3
Force(s)
endeffector, 11-11–13
and torques
acting on link n, 4-3f
between interacting bodies, 7-15–16
and velocity, 5-3–4
Force and metrology loops, 13-5–6
Force and torque, 12-9
Force computation, 5-8–9
Force control block diagram, 16-11f
Force controlled hydraulic manipulator, 21-18f

Force controller
with feed-forward compensation, 18-3f
Force feedback, 19-18–19
Force sensing, 11-18, 23-3
Force sensing resistors (FSR), 11-18
Force sensors, 11-17
Force step-input, 16-11–12
Forward dynamics form, 23-6
Forward dynamics solver, 23-20
Forward kinematics (FK), 14-2
map, 5-4, 17-3–4
Forward-path
block diagram of, 19-8f
Forward recursion, 4-2
Foundation Fieldbus, 26-11
Foundation Trilogy, 1-3
Four bar linkage jaws, 11-10
Four bar linkages gripper arms, 11-4f
4x4 homogeneous transformation, 4-1
Fowardkinematics.c, 3-18, 3-24–25
Frames of reference
assigning, 2-7
Frankenstein, 1-2
Frankenstein, Victor, 1-2
Free-body approach, 4-3
Freedom robot army manipulator, 8-9f
Frequency domain solutions, 24-16–19
Frequency response and impulse response, 24-19
FRFs
magnitude plots of, 15-13f

Friction
in dynamics, 7-21–22
and grasping forces, 11-12–13
Frictional forces, 19-2f
Friction forces, 7-16–17
as result of contact, 7-22f
Friction modeling, 14-5–6
Friction modeling and estimation, 14-19
Friction model validation
torque applied to third joint, 14-20f
Friction parameters estimation, 14-6–7
Friction system
with feedforward compensation
block diagram of, 9-20f
control effort for, 9-22f
response of, 9-22f
without feedforward compensation
control effort in, 9-21f
mass response in, 9-21f
FSR, 11-18
FTA, 25-4
Function block diagram (FBD), 26-15
Furby, 1-11
G
GAAT, 21-3
Gauss-Jordan elimination, 3-26–28
Generalized active force, 6-4
Generalized conditions, 17-5
Generalized inertia force, 6-4
Generalized inertia matrix, 5-6

General Motors (GM), 1-2, 1-5, 1-7
Generating zero vibration commands, 9-5–9
Generic system
block diagram, 9-4f
Generic trajectory command
input shaping, 9-9f
Geodesic equation, 5-10
Geometric interpretation, 5-10–11
Geometric model, 23-17
Geometric vision
survey, 22-1–22
Global proximity test, 23-18
Global warming, 1-3
GM, 1-2, 1-5, 1-7
Golem, 1-1, 1-2
Grafton, Craig, 21-2
Graphical animation, 21-12–13
Graphical user interface (GUI), 26-6
Graphical visualization tools, 21-1
Grasping forces
and friction, 11-12–13
Grasping modes
endeffector, 11-11–13
Grasping stability, 11-11–12
Grasp types
for human hands, 11-12f
Greek mythology, 1-1
Gripper and jaw design geometry, 11-13
Gripper arms
four bar linkages, 11-4f

Gripper design
case study, 11-14–15
products, 11-13–14
Gripper forces and moments, 11-12f
Gripper jaw design algorithms, 11-15–16
Gripper kinematics
endeffector, 11-9–11
Grounded, 23-3
Guaranteed stability of uncertain systems, 17-14
GUI, 26-6
Gunite and associated tank hardware, 21-4f
Gunite and Associated Tanks (GAAT), 21-3
Index I-7
H
Hair transplantation robot, 25-12
Hall effect sensor, 12-8, 12-8f
Haptic interface to virtual environments, 23-1–21, 23-2f
applications, 23-3–4
characterizing human user, 23-5
classification, 23-2–3
design, 23-7–9
related technologies, 23-1–2
specification and design of, 23-5–7
system network diagram and block diagram, 23-5f
system performance metrics and specifications, 23-4–9
Haptic perception in the blind, 23-11
Haptic rendering
block diagram, 23-8f
schematic representation, 23-7f
Haptics

history, 23-10–11
Haptic terms
taxonomy of, 23-3f
HART
sensor-level communications protocol, 26-9–10
HAT controller model
details, 21-19f
HAT manipulator model
details, 21-19f
HAT operator, 22-3
HAT simulation model, 21-18f
Hazard analysis, 25-4–5
initial and final risk legend, 25-5
likelihood determination, 25-5
risk acceptability, 25-5
severity determination, 25-5
verification and validation, 25-4
Hazardous environments, 11-3
Headers
C-code, 3-29
Hebrew mythology, 1-1
HelpMate Robotics, 1-10
Hexaglide mechanism, 9-2f
High end robot simulation packages, 21-7–8
Highway addressable remote transducer (HART)
sensor-level communications protocol, 26-9–10, 26-10f
HMA, 21-3
HMI, 26-6–8
Hohn, Richard, 1-8
Holding torque, 12-14

Holonomic constraints, 5-11, 16-14–16
Homogeneous matrix, 5-2
Homogeneous transformation, 2-6, 2-7
computes
C-code, 3-24–25, 3-25–26
Homogeneous transformation, 4x4, 4-1
Homogeneoustransformation.c, 3-18, 3-25–26
Homogeneous transformation matrices (HTM), 10-8,
10-9, 10-10
algorithm for determining, 8-6–8
Homogeneous vector, 5-2
Homunculus, 1-2
Honda, 1-11
Hooke’slaw,24-2
Hose management arm (HMA), 21-3
HTM. See Homogeneous transformation matrices (HTM)
Human and automatic controller, 23-4
Human force without compensation, 21-20f
Human haptics, 23-9–13
Human-machine interface (HMI), 26-6–8
gas delivery subsystem menu example, 26-7f
Human user
haptic interface to virtual environments, 23-5
Hybrid control, 17-20
Hybrid controller, 26-5
Hybrid impedance control, 16-9–14
type, 16-9–10
Hybrid impedance controller, 16-13f
Hybrid position/force control, 16-6–9, 16-8f
Hybrid system, 17-20

Hybrid type of control algorithms, 20-6
Hydraulic actuators, 12-17. See also HAT controller model
Hydraulic fluid power, 11-8
I
I, Robot, 1-3
Idealized structures and loading, 24-5
IEA, 26-12
IGRIP, 21-7, 21-8
IK. See Inverse kinematics (IK)
Image formation, 22-2–3
Impact equation, 5-13–14
Impedance
vs. admittance regulation, 19-9–10
and interaction control, 19-1–23
Impedance design
for handling an object, 20-7–9
Impulses, 9-6
canceling vibration, 9-6f
Incremental position sensors, 13-11–12
Independent proportional plus derivative joint control,
24-27–29
Inductive (eddy current) sensors, 12-5
Industrial Ethernet Association (IEA), 26-12
Industrial Open Ethernet Association (IOANA), 26-12
Industrial protocol (IP), 26-12
Industrial robot
birth of, 1-4–5
invention, 1-2
Inertia activity, 6-4
Inertial damping controller

arm degrees of freedom augmentation, 24-40
quenching flexible base oscillations, 24-41f
three axis arm as micromanipulator for, 24-41f
Inertial force, 6-4, 19-2f
Inertial reference frame, 4-2
Inertia matrix, 17-5
Inertia tensor, 4-9, 5-6
Infinitesimal motions
and associated Jacobian matrices, 2-8–12
rigid-body, 2-11–12
screw like, 2-11
Infinitesimal twist, 2-11
I-8 Robotics and Automation Handbook
Information networks, 26-12
Inner loop control, 17-8
Inner loop/outer loop, 17-8
architecture, 17-8f
Input/output, 26-8–9, 26-8f
Input shapers, 13-21
sensitivity curves of, 9-10f
Instruction list (IL), 26-16
Integrated end effector attachment, 11-4
Integrated Surgical Systems, Inc., 1-10
Interacting rigid bodies systems dynamics, 7-1–23
Interaction
control implementation, 19-14–15
as disturbance rejection, 19-5
effect on performance and stability, 19-2–3
as modeling uncertainty, 19-5
port admittance, 19-12f

port connection causal analysis, 19-8–9
Interaction calculator, 23-17, 23-19–20
interconnection flowchart, 23-18f
Interchangeable endeffectors, 11-16
International Space Station (ISS), 1-9
Inuit legend, 1-1
Invasive robotic surgery, 25-11
Inverse dynamics, 17-8
computational issues, 4-8
Inverse dynamics form of equations, 24-26
Inverse kinematics (IK), 3-1–30, 14-2
analytical solution techniques, 3-4
dialytical elimination, 3-13
difficulty, 3-1–3
existence and uniqueness of solutions, 3-2–3
map, 17-3–4
numerically solves
n degree of freedom robotic manipulator, 3-19–22
reduction to subproblems, 3-4
solutions, 3-2f
infinite numbers, 3-3f
solution using Newton’s method, 3-14–16
utilizing numerical techniques, 3-13–16
zero reference position method, 3-13
Inversekinematics.c, 3-18–30
Inversekinematics.h, 3-18, 3-30
Inverse matrix
computes
C-code, 3-26–28
IOANA, 26-12

IP, 26-12
Isocenter, 25-9
Isolated link
force and torque balance, 4-3–4
Isolate invariants, 23-12
ISS, 1-9
Ith arm coordinate system, 20-3f
It’sBeenaGoodLife, 1-4
J
Jacobian(s)
associated with parametrized rotations
angular velocity, 2-8–10
constructs approximate
C-code, 3-23–24
manipulator, 17-4
six by six, 3-14, 3-23–24
for ZXZ Euler angles, 2-10–11
Jacobian matrices
adjoint, 2-12
associated
and infinitesimal motions, 2-8–12
body manipulator, 5-5
Jacobian singularities, 3-13
Jacquard, Joseph, 1-2
Japanese Industrial Robot Association (JIRA), 1-7–8
Japanese manufacturers, 1-7
Jaws
design geometry, 11-13
four bar linkage, 11-10
with grasped object, 11-15f

JIRA, 1-7–8
Johnson, Harry, 1-7
Joint errors
ranges of, 15-20f
variances of, 15-21t
Joint motions
online reconstruction of, 14-9–10
7-joint robot manipulator, 8-15–18
Joint space, 17-3
inverse dynamics, 17-8–9
model, 16-2–3
trajectory
for writing task, 14-18f
Joint torques, 4-8
Joint variables, 5-4
K
Kalman filter
bode plots of, 14-10f
Kalman filtering technique, 14-7
Kane, Thomas, 6-1
Kane’s dynamical equations, 6-3
Kane’s equations, 6-4
in robotic literature, 6-22–25
Kane’s method, 4-2, 6-1–29
commercial software packages related, 6-25–29
description, 6-3–4
discrete general steps, 6-5
kinematics, 6-18–22
preliminaries, 6-16–18
Kinematic(s), 17-3–4, 24-9–11

chain, 17-2
closed, 24-10
deformation, 24-10
design, 13-6
and dynamic models in closed form, 14-15–17
interfaces, 23-3
Kane’s method, 6-18–22
modeling, 10-7–12, 14-3–4
simulation, 21-1
Kronecker product of two vectors, 22-5
Kron’s method of subspaces, 7-14