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Chapter 20 — Snake-Like and Continuum Robots

Ian D. Walker, Howie Choset and Gregory S. Chirikjian

This chapter provides an overview of the state of the art of snake-like (backbones comprised of many small links) and continuum (continuous backbone) robots. The history of each of these classes of robot is reviewed, focusing on key hardware developments. A review of the existing theory and algorithms for kinematics for both types of robot is presented, followed by a summary ofmodeling of locomotion for snake-like and continuum mechanisms.

Binary manipulator navigating an obstacle

Author  Greg Chirikjian

Video ID : 163

Simulation of Greg Chirikjian's binary manipulator navigating an obstacle.

Chapter 17 — Limbed Systems

Shuuji Kajita and Christian Ott

A limbed system is a mobile robot with a body, legs and arms. First, its general design process is discussed in Sect. 17.1. Then we consider issues of conceptual design and observe designs of various existing robots in Sect. 17.2. As an example in detail, the design of a humanoid robot HRP-4C is shown in Sect. 17.3. To design a limbed system of good performance, it is important to take into account of actuation and control, like gravity compensation, limit cycle dynamics, template models, and backdrivable actuation. These are discussed in Sect. 17.4.

In Sect. 17.5, we overview divergence of limbed systems. We see odd legged walkers, leg–wheel hybrid robots, leg–arm hybrid robots, tethered walking robots, and wall-climbing robots. To compare limbed systems of different configurations,we can use performance indices such as the gait sensitivity norm, the Froude number, and the specific resistance, etc., which are introduced in Sect. 17.6.

Cybernetic human HRP-4C quick turn

Author  AIST

Video ID : 525

Quick slip-turn of an HRP-4C on its toes developed by Dr. Miura, Dr. Kanehiro, Dr. Kaneko, Dr. Kajita, and Dr. Yokoi.

Chapter 53 — Multiple Mobile Robot Systems

Lynne E. Parker, Daniela Rus and Gaurav S. Sukhatme

Within the context of multiple mobile, and networked robot systems, this chapter explores the current state of the art. After a brief introduction, we first examine architectures for multirobot cooperation, exploring the alternative approaches that have been developed. Next, we explore communications issues and their impact on multirobot teams in Sect. 53.3, followed by a discussion of networked mobile robots in Sect. 53.4. Following this we discuss swarm robot systems in Sect. 53.5 and modular robot systems in Sect. 53.6. While swarm and modular systems typically assume large numbers of homogeneous robots, other types of multirobot systems include heterogeneous robots. We therefore next discuss heterogeneity in cooperative robot teams in Sect. 53.7. Once robot teams allow for individual heterogeneity, issues of task allocation become important; Sect. 53.8 therefore discusses common approaches to task allocation. Section 53.9 discusses the challenges of multirobot learning, and some representative approaches. We outline some of the typical application domains which serve as test beds for multirobot systems research in Sect. 53.10. Finally, we conclude in Sect. 53.11 with some summary remarks and suggestions for further reading.

CKBOTS reconfigurable robots

Author  Mark Yim

Video ID : 196

This video shows reconfigurable robots, which are capable of a variety of configurations and modes of locomotion, including bipeds that can stand up and walk. This system is robust in a variety of situations, as shown in the video. The system has three clusters: when clusters disconnect, they enter a search mode and approach each other to assemble. After successful self-reassembling, the robot system stands up to continue its task.

Chapter 63 — Medical Robotics and Computer-Integrated Surgery

Russell H. Taylor, Arianna Menciassi, Gabor Fichtinger, Paolo Fiorini and Paolo Dario

The growth of medical robotics since the mid- 1980s has been striking. From a few initial efforts in stereotactic brain surgery, orthopaedics, endoscopic surgery, microsurgery, and other areas, the field has expanded to include commercially marketed, clinically deployed systems, and a robust and exponentially expanding research community. This chapter will discuss some major themes and illustrate them with examples from current and past research. Further reading providing a more comprehensive review of this rapidly expanding field is suggested in Sect. 63.4.

Medical robotsmay be classified in many ways: by manipulator design (e.g., kinematics, actuation); by level of autonomy (e.g., preprogrammed versus teleoperation versus constrained cooperative control), by targeted anatomy or technique (e.g., cardiac, intravascular, percutaneous, laparoscopic, microsurgical); or intended operating environment (e.g., in-scanner, conventional operating room). In this chapter, we have chosen to focus on the role of medical robots within the context of larger computer-integrated systems including presurgical planning, intraoperative execution, and postoperative assessment and follow-up.

First, we introduce basic concepts of computerintegrated surgery, discuss critical factors affecting the eventual deployment and acceptance of medical robots, and introduce the basic system paradigms of surgical computer-assisted planning, execution, monitoring, and assessment (surgical CAD/CAM) and surgical assistance. In subsequent sections, we provide an overview of the technology ofmedical robot systems and discuss examples of our basic system paradigms, with brief additional discussion topics of remote telesurgery and robotic surgical simulators. We conclude with some thoughts on future research directions and provide suggested further reading.

CardioArm

Author  Carnegie Mellon University, CNN

Video ID : 829

A robotic snake for heart operations: CardioArm.

Chapter 1 — Robotics and the Handbook

Bruno Siciliano and Oussama Khatib

Robots! Robots on Mars and in oceans, in hospitals and homes, in factories and schools; robots fighting fires, making goods and products, saving time and lives. Robots today are making a considerable impact on many aspects of modern life, from industrial manufacturing to healthcare, transportation, and exploration of the deep space and sea. Tomorrow, robotswill be as pervasive and personal as today’s personal computers. This chapter retraces the evolution of this fascinating field from the ancient to themodern times through a number of milestones: from the first automated mechanical artifact (1400 BC) through the establishment of the robot concept in the 1920s, the realization of the first industrial robots in the 1960s, the definition of robotics science and the birth of an active research community in the 1980s, and the expansion towards the challenges of the human world of the twenty-first century. Robotics in its long journey has inspired this handbook which is organized in three layers: the foundations of robotics science; the consolidated methodologies and technologies of robot design, sensing and perception, manipulation and interfaces, mobile and distributed robotics; the advanced applications of field and service robotics, as well as of human-centered and life-like robotics.

Robots — A 50 year journey

Author  Oussama Khatib

Video ID : 805

In this collection of short segments, this video retraces the history of the most influential modern robots developed in the 20th century (1950-2000). The 50-year journey was first presented at the 2000 IEEE International Conference on Robotics and Automation (ICRA) in San Francisco.

Chapter 25 — Underwater Robots

Hyun-Taek Choi and Junku Yuh

Covering about two-thirds of the earth, the ocean is an enormous system that dominates processes on the Earth and has abundant living and nonliving resources, such as fish and subsea gas and oil. Therefore, it has a great effect on our lives on land, and the importance of the ocean for the future existence of all human beings cannot be overemphasized. However, we have not been able to explore the full depths of the ocean and do not fully understand the complex processes of the ocean. Having said that, underwater robots including remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs) have received much attention since they can be an effective tool to explore the ocean and efficiently utilize the ocean resources. This chapter focuses on design issues of underwater robots including major subsystems such as mechanical systems, power sources, actuators and sensors, computers and communications, software architecture, and manipulators while Chap. 51 covers modeling and control of underwater robots.

Preliminary experimental result of an AUV yShark2

Author  Hyun-Taek Choi

Video ID : 799

This video shows preliminary experimental result of an underwater robot named yShark2 developed by KRISO (Korea Research Institute of Ships and Ocean Engineering). yShark is a test platform and is designed especially for testing the intelligent algorithms we are working on. For this, it has AHRS, IMU, DVL, two cameras, an LED light, a depth sensor, eight-channel ranging sonar as basic navigation sensors, and we can install an imaging sonar DIDSON for obtaining pictures as shown in Fig. 25.2. More importantly, its system software architecture is implemented using the structure explained in Fig. 25.7. The motion in this video is controlled by autonomous algorithms.

Chapter 74 — Learning from Humans

Aude G. Billard, Sylvain Calinon and Rüdiger Dillmann

This chapter surveys the main approaches developed to date to endow robots with the ability to learn from human guidance. The field is best known as robot programming by demonstration, robot learning from/by demonstration, apprenticeship learning and imitation learning. We start with a brief historical overview of the field. We then summarize the various approaches taken to solve four main questions: when, what, who and when to imitate. We emphasize the importance of choosing well the interface and the channels used to convey the demonstrations, with an eye on interfaces providing force control and force feedback. We then review algorithmic approaches to model skills individually and as a compound and algorithms that combine learning from human guidance with reinforcement learning. We close with a look on the use of language to guide teaching and a list of open issues.

Demonstration by visual tracking of gestures

Author  Ales Ude

Video ID : 99

Demonstration by visual tracking of gestures. Reference: A. Ude: Trajectory generation from noisy positions of object features for teaching robot paths, Robot. Auton. Syst. 11(2), 113–127 (1993); URL: http://www.cns.atr.jp/~aude/movies/ .

Chapter 22 — Modular Robots

I-Ming Chen and Mark Yim

This chapter presents a discussion of modular robots from both an industrial and a research point of view. The chapter is divided into four sections, one focusing on existing reconfigurable modular manipulators typically in an industry setting (Sect. 22.2) and another focusing on self-reconfigurable modular robots typically in a research setting (Sect. 22.4). Both sections are sandwiched between the introduction and conclusion sections.

This chapter is focused on design issues. Rather than a survey of existing systems, it presents some of the existing systems in the context of a discussion of the issues and elements in industrial modular robotics and modular robotics research. The reader is encouraged to look at the references for further discussion on any of the presented topics.

ATRON robot showing robust and reversible execution of self-reconfiguration sequences

Author  Ulrik Pagh Schultz

Video ID : 5

ATRON robot showing robust and reversible execution of self-reconfiguration sequences.

Chapter 26 — Flying Robots

Stefan Leutenegger, Christoph Hürzeler, Amanda K. Stowers, Kostas Alexis, Markus W. Achtelik, David Lentink, Paul Y. Oh and Roland Siegwart

Unmanned aircraft systems (UASs) have drawn increasing attention recently, owing to advancements in related research, technology, and applications. While having been deployed successfully in military scenarios for decades, civil use cases have lately been tackled by the robotics research community.

This chapter overviews the core elements of this highly interdisciplinary field; the reader is guided through the design process of aerial robots for various applications starting with a qualitative characterization of different types of UAS. Design and modeling are closely related, forming a typically iterative process of drafting and analyzing the related properties. Therefore, we overview aerodynamics and dynamics, as well as their application to fixed-wing, rotary-wing, and flapping-wing UAS, including related analytical tools and practical guidelines. Respecting use-case-specific requirements and core autonomous robot demands, we finally provide guidelines to related system integration challenges.

Structural, inspection-path planning via iterative, viewpoint resampling with application to aerial robotics

Author  Kostas Alexis

Video ID : 604

This video presents experimental results relevant for the ICRA 2015 paper: A. Bircher, K. Alexis, M. Burri, P. Oettershagen, S. Omari, T. Mantel, R. Siegwart: Structural inspection path planning via iterative viewpoint resampling with application to aerial robotics, IEEE Int. Conf. Robot. Autom. (ICRA), Seattle (2015), pp. 6423 - 6430; doi: 10.1109/ICRA.2015.7140101

Chapter 40 — Mobility and Manipulation

Oliver Brock, Jaeheung Park and Marc Toussaint

Mobile manipulation requires the integration of methodologies from all aspects of robotics. Instead of tackling each aspect in isolation,mobilemanipulation research exploits their interdependence to solve challenging problems. As a result, novel views of long-standing problems emerge. In this chapter, we present these emerging views in the areas of grasping, control, motion generation, learning, and perception. All of these areas must address the shared challenges of high-dimensionality, uncertainty, and task variability. The section on grasping and manipulation describes a trend towards actively leveraging contact and physical and dynamic interactions between hand, object, and environment. Research in control addresses the challenges of appropriately coupling mobility and manipulation. The field of motion generation increasingly blurs the boundaries between control and planning, leading to task-consistent motion in high-dimensional configuration spaces, even in dynamic and partially unknown environments. A key challenge of learning formobilemanipulation consists of identifying the appropriate priors, and we survey recent learning approaches to perception, grasping, motion, and manipulation. Finally, a discussion of promising methods in perception shows how concepts and methods from navigation and active perception are applied.

State-representation learning for robotics

Author  Rico Jonschkowski, Oliver Brock

Video ID : 670

State-representation learning for robotics using prior knowledge about interacting with the physical world.