Author: Jun-Ming Lu, Tzung-Cheng Tsai, Yeh-Liang Hsu (2010-10-05);
recommended: Yeh-Liang Hsu (2010-10-05).
Note: This paper is a chapter
in the book “Talking
about interaction”, to be
between human and robot
With the rapid
advancement of robotics, robots have become smarter and thus develop a closer
relationship with humans over time. To accommodate this strong growth, the
interaction between human and robot plays a major role in the modern
applications of robotics. This multidisciplinary field of research, namely
human-robot interaction (HRI), requires contributions from a variety of
research fields such as robotics, human-computer interaction, and artificial
intelligence. This chapter will first define the two main categories of robots,
namely industrial and service robots, and their applications. Subsequently, the
general HRI issues will be discussed to explain how they affect the use of
robots. Finally, key design elements for good HRI are summarized to reveal the
enabling technologies and future trends in the development of HRI.
robotics; human-robot interaction (HRI); telepresence
1. Robots and robotics
Prior to the use
of the term “robot,” human beings have been dreamed about human-like creations
that can assist in performing tasks for a long time. For example, in 1495,
Leonardo Da Vinci designed a humanoid automaton that is intended to make
several human-like motions (Figure 1). However, due to the technological
limitations, most of these studies remain in conceptual stages. In the 18th
century, miniature automatons come out as toys for entertainment. With the
programmed musical box embedded in a doll, the melody starts to play as if the
doll plays the instrument by itself. In 1920, the term “robot” was first
introduced by Čapek in his play entitled “Rossum's Universal Robots.” Based on
his idea, robots are the artificial people created to work as servants. In the
beginning, the robots are happy to work for the human who invented them.
However, as time goes by, the robots begin to revolt against humans and fight
for their own rights. This play reflects the desire of human to enrich daily
lives through the use of robots, as well as the consequence it may lead to.
From then on, the term “robot” began to be widespread and adopted in many
domains to describe the human-like machines that work to assist humans.
Figure 1. The humanoid automation created by Da
Vinci (Möller, 2005)
In 1927, Roy J.
Wensley invented the humanoid “Televox,” which is likely the first actual robot
and can be controlled by means of specific voice input (Figure 2). Later on,
Elektro was on exhibit at the 1939 New York World's Fair with his mechanical
dog Sparko (Figure 3). He can walk by voice command, speak about 700 words,
smoke cigarettes, and blow up balloons. These brilliant inventions immediately
caught people’s eyes and encouraged them to continue bringing their dreams to
reality. Afterwards, the term “robotics” appeared in the science fiction “I,
Robot” to describe this field of study. The three laws of robotics were also
proposed to address the interaction between robots and human beings (Asimov,
Figure 2. Roy J. Wensley and his humanoid Televox
Figure 3. Elektro (middle) and Sparko (left)
In late 20th
century, a robot was defined as “a reprogrammable and multifunctional
manipulator designed to move materials, parts, tools, or specialized devices
through various programmed motions for the performance of a variety of tasks”
(Robot Institute of America, 1979). Nevertheless, this fails to include the
broad range of robotics in modern development. At present, the robots are more
than agents that help to perform the repetitive works. Moreover, they are
expected to cooperate with human beings. Generally speaking, according to the
application fields, robots can be categorized as industrial robots and service
robots. The different purposes and characteristics of these two types of robots
are discussed in the following context.
1.1 Industrial Robots
(International Standard Organization, 1994) defines an industrial robot as “an
automatically controlled, reprogrammable, and multipurpose manipulator
programmable in three or more axes, which may be either fixed in place or
mobile for use in industrial automation applications.” On the basis of this
concept, industrial robots are intended to assist humans in repetitive tasks,
so that the efficiency can be improved through the automation of manufacturing
processes. For this purpose, industrial robots do not need to resemble real
humans. Instead, they are designed to imitate body movements of humans. Thus,
an industrial robot generally comes in the form of an articulated robotic arm.
Typical applications can be seen in assembly, packaging (Figure 4a), painting
(Figure 4b) and so on. In addition, industrial robots can be seen in the
agricultural (Figure 5a) and food industries (Figure 5b) as well.
Figure 4. (a) An industrial robot for packaging
(Gromyko, 2009); (b) an industrial robot for printing (Schaefer, 2008)
(a) An industrial robot for cookie manufacturing (Garcia et al., 2007); (b) an
agricultural robot for apple grading (Billingsley et al., 2009)
1.2 Service Robots
According to the
International Federation of Robotics (IFR), a service robot is a robot which
operates semi- or fully autonomously to perform services useful to the
well-being of humans and equipment, excluding manufacturing operations.
Generally, service robots include cleaning robots, assistive robots, wheelchair
robots, guide robots, entertainment robots, and educational robots. For
example, Figure 6 depicts a robot suit which helps to enhance the strength of
caregiver (Satoh et al., 2009). Besides, as shown in Figure 7, robotic
wheelchairs with the functions of navigation and motion planning allow people
with limited mobility, such as the elderly and the disabled, to move freely and
easily (Prassler et al., 2001; Pineau and Atrash, 2007).
Robot suit HAL for bathing care assistance (Satoh et al., 2009)
The robotic wheelchairs (a) MAid (Prassler et al., 2001) (b) SmartWheeler
(Pineau and Atrash, 2007)
In addition to
the basic requirements of service robots, the need for robots facilitating
healthcare for the elderly, both physiologically and psychologically, is also
becoming an urgent issue in the aging society. Interactive autonomous robots
behave autonomously using various kinds of sensors and actuators, and can react
to stimulation by its environment, including interacting with a human. Seal
robot Paro is an example of robot-assisted therapy for improving human mind at
hospitals or institutions (Wada et al., 2008), as shown in Figure 8. Besides,
Lytle (2002) reported that Matsushita electrics had developed a robotic care bear
whose purpose was to watch over the elderly residents in a hi-tech retirement
center. These modern applications of service robots significantly improve the quality
of life for the elderly.
Paro interacting with the elderly in a nursing home (Wada et al., 2008)
In health care
applications, telepresence robots, which let a person be in two places at once,
are also of great interest. The remote-controlled robot “Rosie” stands 65
inches tall and has a computer-screen head which serves as a physician’s eyes
and ears, as shown in Figure 9. Its two-way audio and video capabilities enable
individuals to be physically located in one location and virtually present in
another at the same time. The robot allows medical assessments and diagnoses to
take place in real-time. Patient-specific medical data, such as ultrasound
images, can be transmitted through the wireless Internet. Medical personnel can
discuss treatment plans and interact with patients remotely. By serving as an
extension of physician-patient contact, patients feel more satisfied because
physicians seem to spend more time with them (Gerrard et al., 2010).
Figure 9. Physicians operate the robot to visit
patients (Gerrard et al., 2010)
2. Human-robot interaction
As introduced in
section 1, robots are becoming more common and have changed the way we live. In
such an environment, humans need to interact with robots to perform the tasks
or access the service they provide. Thus, the interaction between human and
robot is of great concern in the development of robotics. Human-robot
interaction (HRI) is a multidisciplinary study that requires contributions from
robotics, human-computer interaction, human factors engineering, artificial
intelligence, and some other research fields. The origin of HRI as a discrete
problem can be traced back to Asimov’s three laws of robotics (Asimov, 1941):
robot may not injure a human being or, through inaction, allow a human being to
come to harm.
robot must obey any orders given to it by human beings, except where such
orders would conflict with the First Law.
robot must protect its own existence as long as such protection does not
conflict with the First or Second Law.
These three laws mainly point out the
HRI issue in terms of safety. Under this concept, robot and human should be
regarded as separate individuals that do not conflict with each other. Besides,
in order that a robot can obey the orders given by human beings, a control
mechanism enabling the robot to perceive humans and make responses is required.
Moreover, as humans wish to have human-like robots as assistants or servants,
anthropomorphic characteristics help to meet this expectation. Considering
these issues with respect to human-robot interaction, the associated research
topics will be discussed in the following paragraphs.
Safety is the
primer issue in human-robot interaction. Since robots are designed to assist
humans, they should not bother or even harm humans during operation. In order
to expand safety awareness throughout the robotics industry, the Robotic
Industries Association (RIA) has released ANSI/RIA R15.06 in 1992. It is an
American national standard that provides information and guidance in
safeguarding personnel from injury in robotic-production applications.
Internationally, ISO 10218 (2006) describes the basic hazards associated with
robots and provides requirements to reduce the resulting risks. On the basis of
these standards, researchers and practitioners are striving to provide safety
assessment in the use of robots.
interaction, especially the industrial robots, the hazards may come from impact
or collision, crushing or trapping, and some other accidents. In order to
prevent against the possible accidents and injuries, special attentions should
be given to the workplace layout, sensors, and emergency-off devices of the
workplace layout, humans and robots can be separated in different blocks to
avoid direct contacts. The work envelope of a robot defines the space that it
can reach. Thus, while designing the layout, it is critical to prevent
personnel from entering this dangerous area in case that a collision happens.
In addition, with the support of computer technologies, it is possible to
simulate the physical interaction between humans and robots. For example,
Oberer et al. (2006) used the CAD models of the human operator and the robot to
conduct impact simulation to assess the injury severity for a human operator
Figure 10. Impact simulation (Oberer et al.,
workplace layout helps to eliminate the risk of impact or collision. However,
in most cases, the space is too limited to enable such practices. Thus, it
requires both human and robot to be aware of the possible impacts. For human
operators, warning signs and sounds are usually used to alert them whenever
collision is about to happen. But when the human operator concentrates too much
on the task and fails to detect that, these warning messages won’t work. In
such a condition, providing sensors with the robots gives a feasible solution.
For example, if the robot can “see” the human operator by means of CCD camera
and computer vision techniques, it can stop moving to avoid collision with the
human in time. Moreover, while a robot is approaching the human but both of
them do not notice that, an emergency-off (EMO) device allows a third person to
prevent against the accident. By pushing the EMO button, the power supply of
the robot can be disconnected immediately to ensure the safety of human beings.
control methods are essential for guiding robots to follow the orders given by
human beings. Technically, the means of control depend on the application field
of robots. Autonomous robots are driven by preprogrammed commands. As the power
is turned on, the robot starts to execute the commands and then performs a
series of actions. In such applications, computer programming is of great
concern. However, the robot itself seems not to really make interaction with
human, unless it is equipped with sensors to detect human and make real-time
response. Neves and Oliveira (1997) divide the control system of autonomous
robots into three levels, including reflexive level, reactive level, and
cognitive level. At the reflexive level, robot behaviors are developed in a
pure stimulus-response way, which involves only the sensors. To the reactive
level, actions are quickly made to the pre-defined problems based on a database
of robot behaviors. As the complexity increases and results in heavier computation,
it goes to the cognitive level which requires decision making. Combining these
features, autonomous robots can be intelligent and interact well with the
environment and human. Takahashi et al. (2010) developed a mobile robot for
transport called MKR. MKR is able to identify the obstacles and perform
real-time path planning, so that it can avoid collision with humans or objects,
as shown in Figure 11.
Figure 11. The autonomous robot MKR (Takahashi et
controlled robots, the control panel is either connected to the robot or
located remotely. No matter which approach is adopted, it is necessary to
provide appropriate user interface for control. The key elements to a good
interface design generally depend on the nature of the task and user.
Concerning the task, it needs to be simple and intuitive to avoid possible
errors or mistakes. From the user’s point of view, an operational process that
meets human’s expectation helps to enhance the efficiency of control. This is
in relation to the mental model of the user. Due to the diversity of human
beings, related knowledge of engineering psychology and human factors
engineering should be considered to ensure the usability of interface design.
In addition to the mental factors, physical characteristics of humans are also
important to the success of interface design. For example, the button size is
required to fit the finger size of target users, so that they can perform the
operation smoothly with ease.
Figure 12. The robot controlled by a waistcoat
(Suomela and Halme, 2001)
controlled remotely, which are also referred to as teleoperated robots, involve
more complicated HRI issues rather than interface design. Since the user is not
beside the robot, cameras and microphones are needed to allow the operator to
see and hear exactly what the robot does. In other words, the humans should be
able to feel as if they are present during remote operation. This is known as
“telepresence." In the development of telepresence robots, advanced
devices that provide sensory stimuli are critical. As the user gets more
immersed into the remote environment, the performance of control and
interaction will be better. Adalgeirsson and Breazeal (2010) presented the
design and implementation of MeBot, a robotic platform for socially embodied
telepresence (Figure 13). This telerobot communicates with human by more than
simply audio or video but also expressive gestures and body pose. And it was
found that a more engaging and enjoyable interaction is achieved through this
Figure 13. The telepresence robot MeBot
(Adalgeirsson and Breazeal, 2010)
Since the early
development of robotics, there has been a significant trend toward
anthropomorphizing robots to exhibit human-like appearance and behavior. In
this way, people can interact with robots in the ways that they are familiar
with. As the level of anthropomorphism goes higher, the interaction performance
can be further improved (Li et al., 2010). A simple example can be seen in an
articulated robotic arm, which is based on the structure of the human arm and
serves as a third arm for human to enhance the productivity. From this point of
view, techniques contributing to a higher level of anthropomorphism of robots
play an important role in the study of HRI.
One approach to
make robots more anthropomorphic concentrates on building the appearance,
usually the robot head or face. This is because people generally recognize a
person by the face. If the robot head produces human-like expressions, people
may find it friendlier to interact with. A typical application is the robotic
creature Kismet, an expressive anthropomorphic robot as shown in Figure 14. It
is the first autonomous robot explicitly designed to explore face-to-face interactions
with people (Breazeal, 2002). Besides, Michaud et al. (2005) designed Roball, a
ball-shaped robot, which can effectively draw the attention of young children
and interact with them in simple ways. Figure 15 shows the Roball and the
interaction between a child and Roball.
Figure 14. The sociable robot Kismet (Coradeschi
et al., 2006)
Figure 15. Roball and its interaction with a
child (Michaud et al., 2005)
In addition to a
human-like face, the humanoid body further makes a robot more anthropomorphic.
Combining the robot head with the torso, arms and legs, it comes closer to the
realization of an artificial human. Nevertheless, human-like arms and legs are
not sufficient for a humanoid robot. The robot also needs to have the ability
of mimicking human motions, so that it can move as human does. This is enabled
by collaborative efforts among a number of research fields, such as anatomy,
kinematics and biomechanics. Furthermore, if the robot is intended to make
decision and react to the environment as human does, human behavior modeling
should be taken into consideration as well. As it further relates to the study
of psychology and sociology, the complexity thus increases considerably. Figure
16(a) illustrates the humanoid robot ASIMO developed by Honda, which was
intended to act as a human servant (Garcia et al., 2007). Besides, as shown in
Figure 16(b), Aldebaran Robotics has developed the humanoid robot Nao, which
can interact with both human and robot.
Figure 16. Humanoid robots (a) ASIMO (Garcia et
al., 2007) and (b) Nao (Aldebaran Robotics, 2010)
3. Design elements for good human-robot interaction
In section 2, the major domains of HRI issues and some related
applications, including safety, control, and anthropomorphism have been reviewed.
On the basis of these topics, some design elements contributing to good
human-robot interaction need to be further highlighted for successful
implementation. This section will discuss these design elements along with the
associated technologies and future trends.
Equipped with the capabilities to detect humans or objects in the
environment and to react accordingly, the robot can perform autonomous
behaviors for the safe use and a stronger interaction. In order to enhance the
performance of control, the interface needs to follow the principles of
user-centered design. Further, for a more immersive telepresence, sensory
enhancing elements including stereoscopic and stereophonic perception, as well
as supersensory, can make great contributions to stronger human-robot
interaction. Moreover, through the realization of anthropomorphism, human-robot
interaction will become as natural as interpersonal communication. This can be
achieved by providing humanoid elements and enabling eye contact between human
and robot. Finally, in order to enable seamless dataflow, a robust system for
data transmission should be adopted. Table 1 summarizes these elements and the
TABLE 1. Design elements and associated
technologies for good HRI
sensors and actuator, path planning
human-computer interaction, teleoperation,
Sensory enhancing elements
telepresence, multi-sensory stimulation,
binocular and panoramic vision, stereo audio, virtual reality
humanoid appearance, expression, and motion
camera and screen with specific placement
RF and Internet transmission, time-delay improved
3.1 Autonomous behaviors
In pure human-robot interaction, autonomous
behaviors of the robot are generally designed for the safety of use. For
collision prevention, the active identification of possible obstacles in a
reasonable distance is required. This involves three design elements: the
sensors, an intelligent system for path planning, and the actuators. Yasuda et
al. (2009) applied fuzzy logic to develop strategies for collision prevention
of a powered wheelchair, which is equipped with a laser range sensor and a
position sensitive diode sensor to observe the front and both sides (Figure
17). Combining these elements, the robotic wheelchair can either slow down to
stop or directly modify the path setting to avoid obstacles. Besides, Candido
et al. (2008) proposed a hierarchical motion planner for an autonomous humanoid
robot. Based on this motion planner, the robot can generate a feasible path to
finish its walk without making collision or falls, as shown in Figure 18.
Figure 17. The robotic wheelchair and its
structure of operation (Yasuda et al., 2009)
Figure 18. The humanoid robot that is capable for
path planning (Candido et al., 2008)
As for human-robot-human interaction, in which the
robot serves as an interface for communication between people situated in two
places, the autonomous behaviors become more important for a successful
interaction. In such applications of telepresence robotics, the person who
operates the robot remotely is called the user, whereas the other person
interacting directly with the robot is assigned as a participant. From the
user’s perspective, autonomous behaviors of the robot extends the capability of
projection to operate the robot reliably in a dynamic environment. From the
participant’s view, autonomous behaviors also increase the interactive
capability of the participant as a dialogist. For example, a telepresence robot
with the autonomous behavior of identifying the direction of the participant
who is speaking can assist the remote user to respond more quickly and
properly. This is achieved by adopting cameras, microphones, and a dedicated
software system for recognition.
An interactive museum tour-guide robot, as shown
in Figure 19, was developed by two research projects TOURBOT and WebFAIR funded
by the European Union (Burgard et al., 1999; Schulz et al., 2000; Trahanias et
al., 2005). Thousands of users over the world have experienced controlling this
robot through the web to visit the museum remotely. They developed a modular
and distributed software architecture which integrates localization, mapping,
collision avoidance, planning, and various modules concerned with user
interaction and web-based telepresence. With these autonomous features, the
user can operate the robot to move quickly and safely in a museum crowded with
Figure 19. An interactive museum tour-guide robot
and its GUI (Trahanias et al., 2005)
3.2 User interface
The performance of control mainly depends on the
usability of user interface. The first step toward a usable interface design is
to acquire a detailed understanding the relationship between the user and the
task. This is highly related to the study of human factors engineering, which
aims to develop user-centered design based on scientific evidence. Since the
interface of control for robots is usually established on a computer system,
most of the problems fall within the domain of human-computer interaction
(HCI). There have been numerous ongoing HCI studies that endeavored to
formulate universal principles of interface design. The focus tends to be on
how users can deal with the tasks efficiently without committing errors. To
make the design principles into practice, it also requires efforts from the
fields of computer science and mechanical design. For instance, Baker et al.
(2004) designed the user interface of the robot for search and rescue toward
providing easy and intuitive use. As Figure 20 illustrates, the interface helps
the user to concentrate on the video window without being distracted by
Figure 20. The easy and intuitive control
interface of the robot (Baker et al., 2004)
In addition to these basic requirements of user
interface, there are some more issues to be noted in the modern development of
robotics, especially for those with respect to teleoperators. A teleoperator is
a machine that extends the user’s sensing and manipulating capability to a
location remote from that user. Teleoperation refers to direct and continuous
human control of the teleoperator. Many studies emphasize on enabling the user
to modify the remote environment (Stoker et al., 1995; Engelberger, 2001;
Spudis, 2001), that is, projecting the user to the teleoperator. In order to
provide the user with a better remote interaction, virtual reality can be
applied to create an environment with more realistic immersion. With a
head-mounted display, the user can really feel that he/she is present at the
remote location. Further, wired gloves that offer tactile feedbacks as if the
user really touches what the robot does.
The Full-Immersion Telepresence Testbed (FITT)
developed by NASA, which combines a wearable interface integrating human
perception, cognition and eye-hand coordination skills with a robot’s physical
abilities, as shown in Figure 21, is a recent example of advent in
teleoperation (Rehnmark et al., 2005). The teleoperated master-slave system
Robonaut allows an intuitive, one-to-one mapping between master and slave
motions. The operator uses the FITT wearable interface to remotely control the
Robonaut to follow the operator’s motion fully in simultaneous operation to
perform complex tasks in the international space station.
Figure 21. FITT and Robonaut (Rehnmark et al.,
3.3 Sensory enhancing elements
In telepresence, stereoscopic and stereophonic
elements are often emphasized to create the illusion of remote environment,
which increases the feeling of immersion for the user. For example, the user
can identify the distance between an object and the telepresence robot by
binocular vision (Brooker et al., 1999). In addition, Boutteau et al. (2008)
developed an omnidirectional stereoscopic system for the mobile robot
navigation. As shown in Figure 22, the 360-degree field of view enables the
remote operator to have a more detailed understanding about the environment.
Moreover, the head-related transfer function (HRTF) for stereophonic effect
further enables the user to identify the location and direction of a sound
Figure 22. The robot with a stereoscopic system
(Boutteau et al., 2005)
For teleoperated robots, stereoscopic and
stereophonic elements also help to enhance the feel of presence during
operation. In the design of teleoperators, these elements can be added to
provide stronger interaction by adopting the technologies involved in
telepresence videoconferencing. As many practices show, telepresence
videoconferencing enables the users and the participants to communicate more
efficiently. For example, Lei et al. (2004) proposed a representation and
reconstruction module for an image-based telepresence system, using a
viewpoint-adaptation scheme and an image-based rendering technique. This system
provides life-size views and 3D perception of participants and viewers in real
time and hence improves the interaction.
Supersensory refers to an advanced capability to
modify the remote environment provided by a dexterous robot or a precise
telepresence system. From the user’s view, the user’s manipulative efficiency
for special tasks is enhanced when projecting onto a telepresence robot with
supersensory. Green et al. (1995) developed a telepresence surgery system
integrating vision, hearing and manipulation. It consists of two main modules:
a surgeon’s console and a remote surgical unit located at the surgical table.
The remote unit provides scaled motion, force reflection and minimized friction
for the surgeon to carry out complex tasks with quick, precise motions. Similar
applications of supersensory in telepresence surgery can be also seen in the
studies of Satava (1999), Schurr et al., (2000), and Ballantyne (2002).
Supersensory elements can also provide the user
with a novel immersion feeling in a remote environment. For example, the user
can control the zoom function of the camera on a telepresence robot to observe
the small details of the remote environment, which the user does not normally
see with the naked eye. Intuitive Surgery (2010) developed the da Vinci®
Surgical System through the use of supersensory in telepresence. As Figure 23
shows, the da Vinci Surgical System consists of an ergonomically designed surgeon’s
console, a patient-side cart with four interactive robotic arms, and the
high-performance vision system. Powered by state-of-the-art robotic technology,
the surgeon’s hand movements are scaled, filtered and seamlessly translated
into precise movements.
Figure 23. The da Vinci® Surgical System
(Intuitive Surgery, 2010)
As the robot resembles human more, the human-robot
interaction comes closer to interpersonal communication. Thus, anthropomorphism
of robots helps to enhance the performance of human-robot interaction by means
of creating an environment that humans are more familiar with. Generally, this
is enabled by providing humanoid appearance, expression, and motion. Coradeschi
et al. (2006) addressed that appearance and behaviors of robot are essential in
human-robot interaction. A robot’s appearance influences subject’s impressions,
and it is an important factor in evaluating the interaction. Humanlike
appearance can be deceiving, convincing users that robot can understand and do
much more than they actually can. Observable behaviors are gaze, posture,
movement patterns and linguistic interactions.
Ishiguro created a humanoid robot by copying the
appearance of him. As Figure 24 presents, he constructed this robot with
silicone rubber, pneumatic actuators, powerful electronics, and hair from his
own scalp. Although it is not able to move, this robot however meets the
expectation of mimicking a real person’s appearance (Guizzo, 2010). An
alternative approach to provide a humanoid appearance is by displaying the face
of the remote user on a telepresence robot. For interacting with the
participants, the user’s face displayed on a LCD screen is incorporated in many
telepresence robots. Dr. Robot and the telepresence system PEBBLES both use a
LCD screen to display the user’s face, which allows the participants to realize
whom the telepresence robot represents. The commercial product “Giraffe”
(2007), a remote-controlled mobile video conferencing platform, is also a
telepresence robot application. It is composed of two subsystems: the client
application, and the Giraffe robot itself. On the Giraffe robot, there is a
video screen and camera mounted on an adjustable height robotic base. The user
can move the Giraffe robot from afar using the client application. Software
that runs on a standard PC with a webcam enables the user connects to the
distant Giraffe robot through the Internet for a telepresence interaction.
Figure 24. Ishiguro and the humanoid robot
There are many other solutions for presenting
anthropomorphic elements, such as the humanoid expressions. For example, as
depicted in Figure 14, the humanoid robot Kismet is installed with mechanical
facial expressions to make face-to-face interaction with humans (Breazeal,
2002). Besides, Berns and Hirth (2006) developed a humanoid robot face ROMAN.
As Figure 25 shows, the mechanical structure allows ROMAN to make facial
expressions such as anger, disgust, fear, happiness, sadness and surprise.
Facial expressiveness in humanoid-type robots has received a lot of attention
because it is a key component to developing personal attachment with human
users. From a psychological point of view, using facial expressions is an
effective method to build personal attachment in communicating with a human
Figure 25. The expressive robot head ROMAN (Berns
and Hirth, 2006)
Moreover, human-like motions extend the
anthropomorphism of robots to a higher level. This involves the efforts from
motion capture, biomechanics, kinematics, and statistical methods. For example,
Chen (2010) employed a high-speed video camera to capture the jumping procedure
of human and then conducted kinematic analysis, which helps to develop a human
jumping robot. In addition, Kim et al. (2006) adapted the human motion capture
data and formulated an inverse kinematics problem. By optimizing the problem,
the robot is able to imitate human arm motion.
3.5 Eye contact
Eye contact is an important element in
human-to-human communication. It is a well-known cue for gaining attention and
attracting interest. In human-robot interaction, a robot with eye contact can
make the user feel more familiar and comfortable to interact with. Yamato et
al. (2003) focused on the effect that recommendations made by the agent or robot
had on user decisions, and designed a “color name selection task” to determine
the key factors in designing interactively communicating robots. They used two
robots as the robot/agent for comparison. Based on the experimental results,
eye contact and attention-sharing are considered to be important features of
communications that display and recognize the attention of participants.
In social psychology, joint attention is people
who are communicating with each other frequently focus on the same object. The
joint attention is a mental state where two people not only pay attention to
the same information but also notice the other’s attention to it. Imai et al.
(2003) investigates situated utterance generation in human-robot interaction.
In their study, a person has joint attention with a robot to identify the
object indicated by a situated utterance generation generated by the robot
named Robovie. A psychological experiment was conducted to verify the effect of
eye contact on achieving joint attention. According to the experimental
results, it was found that a relationship developed by eye contact produces a
more fundamental effect on communications than logical reasoning or knowledge
In telepresence applications, eye contact can
increase the immersion feeling of the user and the interactive capability of
the participant as a dialogist. It is very difficult to achieve eye contact
during interpersonal communication between the user and the participant through
a telepresence robot when the face of the user is displayed on a LCD screen,
because the placement of the camera on a telepresence robot is usually on top
of the LCD screen, which hinders direct eye contact between the user and the
participant through the telepresence robot. DVE Telepresence (2005) developed a
novel LCE screen by setting the internal camera just behind the monitor. It
provides natural face-to-face and eye contact communication without causing
eyestrain. By adopting advanced devices like this, it is possible to ensure
high-quality eye contact in robotics, which contributes to a stronger
interaction and enhanced performance.
3.6 Data transmission
The transmission of control commands and sensory
feedback is a basic design element for the connection between human and robot.
Without this back support, it is not possible to realize real-time
teleoperation and telepresence. Thus, the related development in communication
engineering also plays an important role in robotics. Generally, wireless radio
frequency and Internet are used in most telepresence applications, and
dedicated lines are used in specific applications (such as operation in space
and deep sea). For example, Winfield and Holland (2000) proposed a
communication and control infrastructure for distributed mobile robotics through
the use of wireless local area network (WLAN) technology and Internet Protocols
(IPs), which results in a powerful platform for collective or cooperative
robotics. The infrastructure described is equally applicable to tele-operated
mobile robots. In addition, considering cost efficiency and ease of use, Lister
and Wunderlich (2002) made use of radio frequency (RF) for mobile robot
control. They also explored software methods to correct errors that may develop
in RF communication.
In order to realize real-time communications, the
speed of transmission is taken into consideration as well. This is in relation
to the effective techniques in data compression and decompression, error
control, and so on. Combined with adequate algorithms of reactive functions, robots
can respond to the human user in a reasonable time. Nevertheless, the respond
time is not suggested to be as short as possible. Instead, Shiwa et al. (2009)
conducted some experiments and claimed that people prefer one-second delayed
responses from the robot rather than immediate responses. Thus, delaying
strategy is adopted by adding conversational fillers to the robot, so that the
robot seems to make a pause for thinking prior to communicating with the human.
This example shows that the issues in data transmission are related to not only
the speed but also the modality of stimulus presentation.
4. Concluding remarks
Human-robot interaction is a growing field of research and application,
which includes lots of topics and associated challenges. With the multidisciplinary
efforts, there is a global trend toward natural interaction and higher
performance. In this chapter, we discussed the highlighted HRI topics and
related practices to provide conceptual ideas of how interaction affects the
development of robotics. In addition, the according design elements for good
human-robot interaction are also presented to serve as a further reference.
In the future development of human-robot interaction, people are looking
forward to the intelligent robots that can interact with users as human beings
do. However, although anthropomorphic characteristics make the robots more
similar to real humans and thus are appealing to many users, there are still a
number of barriers and challenges to be addressed. As the theory of “uncanny
valley” describes, when robots look and act almost like real humans, it however
causes a response of revulsion among human users and participants (Mori, 1970).
That is to say, human likeness of the robot is not always positively correlated
to the perceived familiarity. If the details of behaviors do not match the high
realism of appearance, the robot will produce a negative impression to humans.
As a result, related technologies are required to cross or avoid the uncanny
One possibility is to develop complete human-like appearance and behaviors
for the robot simultaneously. Nevertheless, there seems a long way to go before
overcoming the difficulties in human modeling and other related technologies.
An alternative is to make the robot as an agent of the distant user by
implementing telepresence and teleoperation. Enabled by telepresence, the human
users on both sides appear to communicate with each other by means of
one-to-one-scale video in real time. Then the robots reproduce the actions that
the distant user intended to perform via teleoperation. In this way, it is also
similar to the real human-to-human interaction, although the anthropomorphism
of the robot is not really in a high level.
Last but not least, no matter how closely a robot resembles a real human or
how powerful it is, safety will always be the most essential issue in
human-robot interaction. As Asimov’s three laws of human-robot interaction
indicate, human and robot must cooperate with each other upon the principle of
not conflicting with each other. After all, it may go back to the ethics and
morality with regard to human interaction, just as the relationships among
human beings that we have gotten used to.
and Breazeal, C: 2010, MeBot: A robotic platform for socially embodied
telepresence, Proceedings of the 5th ACM/IEEE International Conference on
Human-Robot Interaction: 15-22, Osaka, Japan.
Robotics: 2010, retrieved from http://www.aldebaran-robotics.com/
Asimov, I: 1942,
Runaround, Street & Smith Press, United States.
Baker, M, Casey,
R, Keyes, B and Yanco, HA: 2004, Improved Interfaces for Human-Robot
Interaction in Urban Search and Rescue, Proceedings of the IEEE International
Conference on Systems, Man and Cybernetics, Hague, the Netherlands.
2002: Robotic surgery, telerobotic surgery, telepresence, and telementoring -
Review of early clinical results, Surgical Endoscopy and Other Interventional
Techniques 16(10): 1389-1402.
Berns, K and
Hirth, J: 2006, Control of facial expressions of the humanoid robot head ROMAN,
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and
Systems: 3119-3124, Beijing, China.
Oetomo, D and Reid, J: 2009, Agricultural robotics, IEEE Robotics & Automation
Magazine 16(4): 16-16, 19.
Savatier, X, Ertaud, JY and Mazari, B: 2008, An omnidirectional stereoscopic
system for mobile robot navigation, Proceedings of the International Workshop
on Robotic and Sensors Environments (ROSE): 138-143, Ottawa, Canada.
2002, Designing Sociable Robots, The MIT Press.
Sharkey, PM, Wann, JP, and Plooy, AM: 1999, A helmet mounted display system
with active gaze control for visual telepresence, Mechatronics 9(7): 703-716.
Burgard, W, Cremers,
AB, Fox, D, Hahnel, D, Lakemeyer, G, Schulz, D, Steiner, W, and Thrun, S: 1999,
Experiences with an interactive museum tour-guide robot, Artificial
Intelligence 114(1-2): 3-55.
Candido, S, Kim,
YT and Hutchinson, S: 2008, An Improved Hierarchical Motion Planner for
Humanoid Robots, Proceedings of the IEEE-RAS International Conference on
Humanoid Robots (Humanoids), Daejeon, Korea.
Chen Y: 2010,
Motion mechanism and simulation of the human jumping robot, Proceedings of the
International Conference on Computer Design and Applications (ICCDA) 3:
361-364, Qinhuangdao, China
Ishiguro, H, Asada, M, Shapiro, SC, Thielscher, M, Breazeal, C, Mataric, MJ,
and Ishida, H: 2006, Human-Inspired Robots, IEEE Intelligent Systems 21(4):
2001, NASA's Robonaut, Industrial Robot 28(1): 35-39.
Jimenez, MA, De Santos, PG and Armada, M: 2007, The evolution of robotics
research, IEEE Robotics & Automation Magazine 14(1): 90-103.
Tusia, J, Pomeroy, B, Dower, A and Gillis, J: 2010, On-call physician-robot
dispatched to remote Labrador, News in Health, Media Centre, Dalhousie
Green, PS, Hill,
JW, Jensen, JF, and Shah, A: 1995, Telepresence surgery, IEEE Engineering in
Medicine and Biology Magazine 14(3): 324-329.
2009, Palletising_robot.jpg, retrieved from: http://commons.wikimedia.org/wiki/
Guizzo, E: 2010,
The man who made a copy of himself, IEEE Spectrum 47(4): 44 – 56.
2002, Scalable multichannel coding with HRTF enhancement for DVD and virtual
sound systems, Journal of the Audio Engineering Society 50(11): 894-913.
2009, TelevoxWensley21Feb1928.jpg, retrieved from:
Imai, M, Ono, T,
and Ishiguro, H: 2003, Physical relation and expression: joint attention for
human-robot interaction, IEEE Transactions on Industrial Electronics 50(4):
Standard Organization: 1994, ISO 8373: Manipulating industrial robots –
Standard Organization: 2006, ISO 10218-1: Robots for industrial environments -
Safety requirements - Part 1: Robot.
Surgical: 2010, da Vinci® Surgical System,
Kim, CH, Kim, D
and Oh, YH: 2006, Adaptation of human motion capture data to humanoid robots
for motion imitation using optimization, Journal of Integrated Computer-Aided
Engineering 13(4): 377-389.
Lei, BJ, Chang,
C, and Hendriks, EA: 2004, An efficient image-based telepresence system for
videoconferencing, IEEE Transactions on Circuits and Systems for Video
Technology 14(3): 335-347.
Li, D, Rau PL,
and Li, Y: 2010, A Cross-cultural Study: Effect of Robot Appearance and Task,
International Journal of Social Robotics 2(2): 175-186.
Lister, MB and
Wunderlich, JT: 2002, Development of software for mobile robot control over a
radio frequency communications link, Proceedings of IEEE Southeast Conference:
414 – 417, Columbia, United States.
Lytle, JM: 2002,
Robot care bears for the elderly, BBC News, Thursday, 21 February, 2002.
2006, Elektro and Sparko, retrieved from: http://www.flickr.com/photos/
Möller, E: 2005,
Leonardo-Robot3.jpg, retrieved from
Mori, M: 1970,
The uncanny valley, Energy 7(4): 33-35.
Neves, M and
Oliveira, E: 1997, A control architecture for an autonomous mobile robot,
Proceedings of First International Conference on Autonomous Agents, California,
Malosio, M, and Schraft, RD: 2006, Investigation of Robot-Human Impact,
Proceedings of the Joint Conference on Robotics 87-103.
Pineau, J and
Atrash, A: 2007, SmartWheeler: A robotic wheelchair test-bed for investigating
new models of human-robot interaction, AAAI Spring Symposium on
Multidisciplinary Collaboration for Socially Assistive Robotics.
Scholz, J, and Fiorini, P: 2001, A robotics wheelchair for crowded public
environment, IEEE Robotics & Automation Magazine 8(1): 38-45
Bluethmann, W, Mehling, J, Ambrose, RO, Diftler, M, Chu, M, and Necessary, R:
2005, Robonaut: the ‘short list’ of technology hurdles, Computer 38(1): 28-37.
of America: 1979, RIA Worldwide Robotics Survey and Directory, Robotic
Institute of America, P.O. Box 1366, Dearborn, Michigan, U.S.A.
1999, Emerging technologies for surgery in the 21st century, Archives of
Surgery 134(11): 1197-1202.
Kawabata, T and Sankai, Y: 2009, Bathing care assistance with robot suit HAL,
Proceedings of IEEE International Conference on Robotics and Biomimetics,
498-503, Guilin, China.
2008, Bios_robotlab_writing_robot.jpg, retrieved from:
Burgard, W, Fox, D, Thrun, S, and Cremers, AB: 2000, Web interfaces for mobile
robots in public places, IEEE Robotics & Automation magazine 7(1): 48-56.
Buess, G, Neisius, B, and Voges, U: 2000, Robotics and telemanipulation
technologies for endoscopic surgery - A review of the ARTEMIS project, Surgical
Endoscopy and other Interventional Techniques 14(4): 375-381.
Spudis PD: 2001,
The case for renewed human exploration of the Moon, Earth Moon and Planets
Burch, DR, Hine, BP III, and Barry, J: 1995, Antarctic undersea exploration
using a robotic submarine with a telepresence user interface, IEEE Expert
Suomela, J and
Halme, A: 2001, Cognitive Human Machine Interface Of Workpartner Robot,
Proceedings of Intelligent
Autonomous Vehicles 2001 Conference (IAV2001), Sapporo, Japan.
Suzuki, T, Shitamoto, H, Moriguchi, T and Yoshida, K: 2010, Developing a mobile
robot for transport applications in the hospital domain, Robotics and
Autonomous Systems 58(7): 889-899.
Industries Association: 1992, ANSI/RIA R15.06: Industrial Robots and Robot
Systems - Safety Requirements, ANSI Standard.
Burgard, W, Argyros, A, Hahnel, D, Baltzakis, H, Pfaff, P, and Stachniss, C:
2005, TOURBOT and WebFAIR: Web-operated mobile robots for tele-presence in
populated exhibitions, IEEE Robotics & Automation Magazine 12(2): 77-89.
Shibata, T, Musha, T and Kimura, S: 2008, Robot therapy for elders affected by
dementia, IEEE Engineering in Medicine and Biology Magazine 27(4): 53 – 60.
and Holland, OE: 2000, The application of wireless local area network
technology to the control of mobile robots, Microprocessors and Microsystems
Brooks, R, Shinozawa, K, and Naya, F: 2003, Human-Robot Dynamic Social
Interaction, NTT Technical Review 1(6): 37-43.
Yasuda, T, Suehiro,
N and Tanaka, K: 2009, Strategies for collision prevention of a compact powered
wheelchair using SOKUIKI sensor and applying fuzzy theory, IEEE International
Conference on Robotics and Biomimetics (ROBIO): 202 – 208, Guilin, China.
Jun-Ming Lu received his Ph.D. degree in
industrial engineering and engineering management from National Tsing Hua
University, Taiwan, in 2009. He is currently a postdoctoral researcher in
Gerontechnology Research Center, Yuan Ze University. His research interests are
ergonomics, digital human modeling, and gerontechnology.
Tzung-Cheng Tsai received his Ph.D. degree in
mechanical engineering from Yuan Ze University, Taiwan, in 2007. He is
currently a researcher in Green Energy & Environment Research Laboratories,
Industrial Technology Research Institute, Taiwan. His research interests are
telepresence, teleoperation, and green energy.
Yeh-Liang Hsu received his Ph.D. degree in
mechanical engineering from Stanford University, United States, in 1992. He is
currently a professor in Department of Mechanical Engineering, the director of
Gerontechnology Research Center, and the secretary general of Yuan Ze
University, Taiwan. His research interests are mechanical design, design optimization,