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Chapter 44 — Networked Robots

Dezhen Song, Ken Goldberg and Nak-Young Chong

As of 2013, almost all robots have access to computer networks that offer extensive computing, memory, and other resources that can dramatically improve performance. The underlying enabling framework is the focus of this chapter: networked robots. Networked robots trace their origin to telerobots or remotely controlled robots. Telerobots are widely used to explore undersea terrains and outer space, to defuse bombs and to clean up hazardous waste. Until 1994, telerobots were accessible only to trained and trusted experts through dedicated communication channels. This chapter will describe relevant network technology, the history of networked robots as it evolves from teleoperation to cloud robotics, properties of networked robots, how to build a networked robot, example systems. Later in the chapter, we focus on the recent progress on cloud robotics, and topics for future research.

Teleoperation of a mini-excavator

Author  Keyvan Hashtrudi-Zaad, Simon P. DiMaio, Septimiu E. Salcudean

Video ID : 82

Teleoperation of a mini-excavator over the internet using a virtual master environment. This video is illustrates how a virtual-reality-based interface can assist users to comprehend robotic states. (See m. 44.4.3 of the Springer Handbook of Robotics, 2nd ed (2006) for details).

Chapter 72 — Social Robotics

Cynthia Breazeal, Kerstin Dautenhahn and Takayuki Kanda

This chapter surveys some of the principal research trends in Social Robotics and its application to human–robot interaction (HRI). Social (or Sociable) robots are designed to interact with people in a natural, interpersonal manner – often to achieve positive outcomes in diverse applications such as education, health, quality of life, entertainment, communication, and tasks requiring collaborative teamwork. The long-term goal of creating social robots that are competent and capable partners for people is quite a challenging task. They will need to be able to communicate naturally with people using both verbal and nonverbal signals. They will need to engage us not only on a cognitive level, but on an emotional level as well in order to provide effective social and task-related support to people. They will need a wide range of socialcognitive skills and a theory of other minds to understand human behavior, and to be intuitively understood by people. A deep understanding of human intelligence and behavior across multiple dimensions (i. e., cognitive, affective, physical, social, etc.) is necessary in order to design robots that can successfully play a beneficial role in the daily lives of people. This requires a multidisciplinary approach where the design of social robot technologies and methodologies are informed by robotics, artificial intelligence, psychology, neuroscience, human factors, design, anthropology, and more.

Learning how to be a learning companion for children

Author  Cynthia Breazeal

Video ID : 560

This video demonstration describes a project whereby we train a policy via learning-by-demonstration for a social robot to serve as a learning companion for young children during free-form educational play. Training data was captured during a Wizard-of-Oz paradigm where the robot played the color-mixing game app with 183 children. Once the model was trained on this data, we did a human-participant study with 85 children to compare the behavior and efficacy of the autonomous robot versus a Wizard-of-Oz-controlled robot. We also compared the children's behavior to just playing the game app without a robot learning companion. We found that the presence of the robot learning companion resulted in deeper exploration of the subject matter of the app (color mixing) and more behaviors targeted to this activity (e.g., there was more random tapping of the app when the robot was not present). The autonomous robot's behavior was not statistically different from the Wizard-of-Oz-controlled robot.

Chapter 36 — Motion for Manipulation Tasks

James Kuffner and Jing Xiao

This chapter serves as an introduction to Part D by giving an overview of motion generation and control strategies in the context of robotic manipulation tasks. Automatic control ranging from the abstract, high-level task specification down to fine-grained feedback at the task interface are considered. Some of the important issues include modeling of the interfaces between the robot and the environment at the different time scales of motion and incorporating sensing and feedback. Manipulation planning is introduced as an extension to the basic motion planning problem, which can be modeled as a hybrid system of continuous configuration spaces arising from the act of grasping and moving parts in the environment. The important example of assembly motion is discussed through the analysis of contact states and compliant motion control. Finally, methods aimed at integrating global planning with state feedback control are summarized.

Demonstration of multisensor integration in industrial manipulation

Author  Torsten Kröger et al.

Video ID : 361

This video demonstrates the potential of multisensor integration in industrial manipulation. A robot is programmed to play the Jenga game. Two cameras are mounted on the manipulator to calculate the positions of all cuboids online. A 6-DOF force/torque sensor and a 6-DOF acceleration sensor are mounted between a hand and gripper to give force/tactile feedback. The manipulator randomly chooses one block and tries to push it out and then put it on the top of the tower. In this video, a record of putting 29 blocks onto the top of the tower is achieved.

Chapter 54 — Industrial Robotics

Martin Hägele, Klas Nilsson, J. Norberto Pires and Rainer Bischoff

Much of the technology that makes robots reliable, human friendly, and adaptable for numerous applications has emerged from manufacturers of industrial robots. With an estimated installation base in 2014 of about 1:5million units, some 171 000 new installations in that year and an annual turnover of the robotics industry estimated to be US$ 32 billion, industrial robots are by far the largest commercial application of robotics technology today.

The foundations for robot motion planning and control were initially developed with industrial applications in mind. These applications deserve special attention in order to understand the origin of robotics science and to appreciate the many unsolved problems that still prevent the wider use of robots in today’s agile manufacturing environments. In this chapter, we present a brief history and descriptions of typical industrial robotics applications and at the same time we address current critical state-of-the-art technological developments. We show how robots with differentmechanisms fit different applications and how applications are further enabled by latest technologies, often adopted from technological fields outside manufacturing automation.

We will first present a brief historical introduction to industrial robotics with a selection of contemporary application examples which at the same time refer to a critical key technology. Then, the basic principles that are used in industrial robotics and a review of programming methods will be presented. We will also introduce the topic of system integration particularly from a data integration point of view. The chapter will be closed with an outlook based on a presentation of some unsolved problems that currently inhibit wider use of industrial robots.

SMErobotics Demonstrator D1 assembly with dual-arm industrial manipulators

Author  Martin Haegele, Thilo Zimmermann, Björn Kahl

Video ID : 380

SMErobotics: Europe's leading robot manufacturers and research institutes have teamed up with the European Robotics Initiative for Strengthening the Competitiveness of SMEs in Manufacturing - to make the vision of cognitive robotics a reality in a key segment of EU manufacturing. Funded by the European Union 7th Framework Programme under GA number 287787. Project runtime: 01.01.2012 - 30.06.2016 For a general introduction, please also watch the general SMErobotics project video (ID 260). About this video: Chapter 1: Introduction (0:00); Chapter 2: Fenceless approach in a safe; environment & Gesture Control (00:27); Chapter 3: Cooperative motion (00:57); Chapter 4: Minimal fixtures for maximum flexibility (Scan Objects) (01:36); Chapter 5: Offline preview (02:12); Chapter 6: Task execution (02:26); Chapter 7: Tool changer device (03:49); Chapter 8: Statement (04:11); Chapter 9: Outro (04:39); Chapter 10: The Consortium (05:08). For details, please visit: http://www.smerobotics.org/project/video-of-demonstrator-d1.html

Chapter 47 — Motion Planning and Obstacle Avoidance

Javier Minguez, Florant Lamiraux and Jean-Paul Laumond

This chapter describes motion planning and obstacle avoidance for mobile robots. We will see how the two areas do not share the same modeling background. From the very beginning of motion planning, research has been dominated by computer sciences. Researchers aim at devising well-grounded algorithms with well-understood completeness and exactness properties.

The challenge of this chapter is to present both nonholonomic motion planning (Sects. 47.1–47.6) and obstacle avoidance (Sects. 47.7–47.10) issues. Section 47.11 reviews recent successful approaches that tend to embrace the whole problemofmotion planning and motion control. These approaches benefit from both nonholonomic motion planning and obstacle avoidance methods.

Mobile-robot, autonomous navigation in Gracia district, Barcelona

Author  Joan Perez

Video ID : 712

This video demonstrates a fully autonomous navigation solution for mobile robots operating in urban pedestrian areas. Path planning is performed by a graph search on a discretized grid of the workspace. Obstacle avoidance is performed by a slightly modified version of the dynamic-window approach.

Chapter 9 — Force Control

Luigi Villani and Joris De Schutter

A fundamental requirement for the success of a manipulation task is the capability to handle the physical contact between a robot and the environment. Pure motion control turns out to be inadequate because the unavoidable modeling errors and uncertainties may cause a rise of the contact force, ultimately leading to an unstable behavior during the interaction, especially in the presence of rigid environments. Force feedback and force control becomes mandatory to achieve a robust and versatile behavior of a robotic system in poorly structured environments as well as safe and dependable operation in the presence of humans. This chapter starts from the analysis of indirect force control strategies, conceived to keep the contact forces limited by ensuring a suitable compliant behavior to the end effector, without requiring an accurate model of the environment. Then the problem of interaction tasks modeling is analyzed, considering both the case of a rigid environment and the case of a compliant environment. For the specification of an interaction task, natural constraints set by the task geometry and artificial constraints set by the control strategy are established, with respect to suitable task frames. This formulation is the essential premise to the synthesis of hybrid force/motion control schemes.

Compliant robot motion: Control and task specification

Author  Joris De Schutter

Video ID : 687

The video contains work developed in the PhD thesis of Joris De Schutter, where the concept of compliant motion based on external force feedback loops and on the task frame formalism to specify interaction tasks were introduced. The video was recorded in 1984. The references for this video are 1. J. De Schutter, H. Van Brussel: Compliant robot motion II. A control approach based on external control loops, Int. J. Robot. Res. 7(4), 18-33 (1988) 2. J. De Schutter, H. Van Brussel: Compliant robot motion I. A formalism for specifying compliant motion tasks, Int. J. Robot. Res. 7(4), 3-17 (1988)

Chapter 30 — Sonar Sensing

Lindsay Kleeman and Roman Kuc

Sonar or ultrasonic sensing uses the propagation of acoustic energy at higher frequencies than normal hearing to extract information from the environment. This chapter presents the fundamentals and physics of sonar sensing for object localization, landmark measurement and classification in robotics applications. The source of sonar artifacts is explained and how they can be dealt with. Different ultrasonic transducer technologies are outlined with their main characteristics highlighted.

Sonar systems are described that range in sophistication from low-cost threshold-based ranging modules to multitransducer multipulse configurations with associated signal processing requirements capable of accurate range and bearing measurement, interference rejection, motion compensation, and target classification. Continuous-transmission frequency-modulated (CTFM) systems are introduced and their ability to improve target sensitivity in the presence of noise is discussed. Various sonar ring designs that provide rapid surrounding environmental coverage are described in conjunction with mapping results. Finally the chapter ends with a discussion of biomimetic sonar, which draws inspiration from animals such as bats and dolphins.

B-scan image of indoor potted tree using multipulse sonar

Author  Roman Kuc

Video ID : 315

By repeatedly clearing the conventional sonar ranging board, each echo produces a spike sequence that is related to the echo amplitude. A brightness-scan (B-scan) image - similar to diagnostic ultrasound images - is generated by transforming the short-term spike density into a gray scale intensity. The video shows a B-scan of a potted tree in an indoor environment containing a doorway (with door knob) and a tree located in front of a cinder-block wall. The B-scan shows the specular environmental features as well as the random tree-leaf structures. Note that the wall behind the tree is also clearly imaged. Reference: R. Kuc: Generating B-scans of the environment with a conventional sonar, IEEE Sensor. J. 8(2), 151 - 160 (2008); doi: 10.1109/JSEN.2007.908242 .

Chapter 27 — Micro-/Nanorobots

Bradley J. Nelson, Lixin Dong and Fumihito Arai

The field of microrobotics covers the robotic manipulation of objects with dimensions in the millimeter to micron range as well as the design and fabrication of autonomous robotic agents that fall within this size range. Nanorobotics is defined in the same way only for dimensions smaller than a micron. With the ability to position and orient objects with micron- and nanometer-scale dimensions, manipulation at each of these scales is a promising way to enable the assembly of micro- and nanosystems, including micro- and nanorobots.

This chapter overviews the state of the art of both micro- and nanorobotics, outlines scaling effects, actuation, and sensing and fabrication at these scales, and focuses on micro- and nanorobotic manipulation systems and their application in microassembly, biotechnology, and the construction and characterization of micro and nanoelectromechanical systems (MEMS/NEMS). Material science, biotechnology, and micro- and nanoelectronics will also benefit from advances in these areas of robotics.

High-speed magnetic microrobot actuation in a microfluidic chip by a fine V-groove surface

Author  Fumihito Arai

Video ID : 491

This video shows high-speed microrobotic actuation driven by permanent magnets in a microfluidic chip. The microrobot has a milliNewton-level output force from a permanent magnet, micrometer-level positioning accuracy, and drive speed of over 280 mm/s. The riblet surface, which is a regularly arrayed V-groove, reduces fluid friction and enables high-speed actuation. Ni- and Si-composite fabrication was employed to form the optimum riblet shape on the microrobot’s surface by wet and dry etching. The evaluation experiments show that the microrobot can be actuated at a rate of up to 90 Hz, which is more than ten times higher than that of the microrobot without a riblet.

Chapter 19 — Robot Hands

Claudio Melchiorri and Makoto Kaneko

Multifingered robot hands have a potential capability for achieving dexterous manipulation of objects by using rolling and sliding motions. This chapter addresses design, actuation, sensing and control of multifingered robot hands. From the design viewpoint, they have a strong constraint in actuator implementation due to the space limitation in each joint. After briefly introducing the overview of anthropomorphic end-effector and its dexterity in Sect. 19.1, various approaches for actuation are provided with their advantages and disadvantages in Sect. 19.2. The key classification is (1) remote actuation or build-in actuation and (2) the relationship between the number of joints and the number of actuator. In Sect. 19.3, actuators and sensors used for multifingered hands are described. In Sect. 19.4, modeling and control are introduced by considering both dynamic effects and friction. Applications and trends are given in Sect. 19.5. Finally, this chapter is closed with conclusions and further reading.

The Dexmart Hand

Author  Claudio Melchiorri

Video ID : 767

Grasp and manipulation tasks executed by the Dexmart Hand, an anthropomorphic robot hand developed within an European research activity. Detailed aspects of the "twisted-spring" actuation principle are demonstrated.

Chapter 69 — Physical Human-Robot Interaction

Sami Haddadin and Elizabeth Croft

Over the last two decades, the foundations for physical human–robot interaction (pHRI) have evolved from successful developments in mechatronics, control, and planning, leading toward safer lightweight robot designs and interaction control schemes that advance beyond the current capacities of existing high-payload and highprecision position-controlled industrial robots. Based on their ability to sense physical interaction, render compliant behavior along the robot structure, plan motions that respect human preferences, and generate interaction plans for collaboration and coaction with humans, these novel robots have opened up novel and unforeseen application domains, and have advanced the field of human safety in robotics.

This chapter gives an overview on the state of the art in pHRI as of the date of publication. First, the advances in human safety are outlined, addressing topics in human injury analysis in robotics and safety standards for pHRI. Then, the foundations of human-friendly robot design, including the development of lightweight and intrinsically flexible force/torque-controlled machines together with the required perception abilities for interaction are introduced. Subsequently, motionplanning techniques for human environments, including the domains of biomechanically safe, risk-metric-based, human-aware planning are covered. Finally, the rather recent problem of interaction planning is summarized, including the issues of collaborative action planning, the definition of the interaction planning problem, and an introduction to robot reflexes and reactive control architecture for pHRI.

Generation of human-care behaviors by human-interactive robot RI-MAN

Author  Masaki Onishi, Tadashi Odashima, Shinya Hirano, Kenji Tahara, Toshiharu Mukai

Video ID : 607

This video shows the the realization of environmental interactive tasks, such as human-care tasks, by replaying the human motion repeatedly. A novel motion-generation approach is shown to integrate the cognitive information into the mimicking of human motions so as to realize the final complex task by the robot. Reference: M. Onishi, Z.W. Luo, T. Odashima, S. Hirano, K. Tahara, T. Mukai: Generation of human care behaviors by human-interactive robot RI-MAN, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), Rome (2007), pp. 3128-3129; doi: 10.1109/ROBOT.2007.363950.