View Chapter

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.

Biped running robot MABEL

Author  Jessy Grizzle

Video ID : 533

A biped running robot MABEL developed at the University of Michigan in the lab of Prof. Grizzle. The robot was developed in collaboration with Jonathan Hurst, Al Rizzi and Jessica Hodgins of the Robotics Institute, Carnegie Mellon University.

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.

Robot for single-port surgery by the University of Nebraska

Author  University of Nebraska Medical Center

Video ID : 827

Robot for single-port surgery by the University of Nebraska: The video includes an explanation of the working principle, tests, and comments by clinicians.

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 results of sonar-based SLAM using landmarks

Author  Hyun-Taek Choi

Video ID : 794

This video records preliminary experimental results of a sonar-based SLAM algorithm developed by KRISO (Korea Research Institute of Ships and Ocean Engineering). A position obtained by the proposed probability-based landmark-recognition method and landmarks especially designed for sonar is used to correct the position estimated by IMU/DVL navigation using EKF (extended Kalman filter).

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.

Formation control via a distributed controller-observer

Author  Gianluca Antonelli, Filippo Arrichiello, Fabrizio Caccavale, Alessandro Marino

Video ID : 293

This video shows an experiment of formation control with a multirobot system composed of Khepera III mobile robots using the distributed controller-observer schema.

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.

Concentric tube robot at TEDMED 2010

Author  Pierre Dupont

Video ID : 252

This video was recorded at TEDMED 2010 in San Diego and features a teleoperated, concentric tube robot with 1 mm- wide forceps solving a miniature version of the puzzle Kanoodle.

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.

The power of prediction: Robots that read intentions

Author  E. Bicho , W. Erlhagen , E. Sousa , L. Louro , N. Hipolito , E.C. Silva , R. Silva , F. Ferreira , T. Machado , M. Hulstijn , Y.Maas , E. de Bruijn , R.H. Cuijpers , R. Newman-Norlund , H. van Schie, R.G.J. Meulenbroek , H. Bekkering

Video ID : 617

Action and intention understanding are critical components of efficient joint action. In the context of the EU Integrated Project JAST, the authors have developed an anthropomorphic robot endowed with these cognitive capacities. This project and the respective robot (ARoS) is the focus of the video. More specifically, the results illustrate crucial cognitive capacities for efficient and successful human-robot collaboration, such as goal inference, error detection, and anticipatory-action selection.

Chapter 67 — Humanoids

Paul Fitzpatrick, Kensuke Harada, Charles C. Kemp, Yoshio Matsumoto, Kazuhito Yokoi and Eiichi Yoshida

Humanoid robots selectively immitate aspects of human form and behavior. Humanoids come in a variety of shapes and sizes, from complete human-size legged robots to isolated robotic heads with human-like sensing and expression. This chapter highlights significant humanoid platforms and achievements, and discusses some of the underlying goals behind this area of robotics. Humanoids tend to require the integration ofmany of the methods covered in detail within other chapters of this handbook, so this chapter focuses on distinctive aspects of humanoid robotics with liberal cross-referencing.

This chapter examines what motivates researchers to pursue humanoid robotics, and provides a taste of the evolution of this field over time. It summarizes work on legged humanoid locomotion, whole-body activities, and approaches to human–robot communication. It concludes with a brief discussion of factors that may influence the future of humanoid robots.

Regrasp planning for pivoting manipulation by a humanoid robot

Author  Eiichi Yoshida

Video ID : 599

The pivoting manipulation presented in video 597 is extended for the humanoid robot to carry a bulky object in a constrained environment. Using multiple roadmaps with different grasping positions and free walking motions, the humanoid robot can set down the object near narrow places and then regrasp it from another position to move the object to the goal.

Chapter 21 — Actuators for Soft Robotics

Alin Albu-Schäffer and Antonio Bicchi

Although we do not know as yet how robots of the future will look like exactly, most of us are sure that they will not resemble the heavy, bulky, rigid machines dangerously moving around in old fashioned industrial automation. There is a growing consensus, in the research community as well as in expectations from the public, that robots of the next generation will be physically compliant and adaptable machines, closely interacting with humans and moving safely, smoothly and efficiently - in other terms, robots will be soft.

This chapter discusses the design, modeling and control of actuators for the new generation of soft robots, which can replace conventional actuators in applications where rigidity is not the first and foremost concern in performance. The chapter focuses on the technology, modeling, and control of lumped parameters of soft robotics, that is, systems of discrete, interconnected, and compliant elements. Distributed parameters, snakelike and continuum soft robotics, are presented in Chap. 20, while Chap. 23 discusses in detail the biomimetic motivations that are often behind soft robotics.

DLR Hand Arm System smashed with baseball bat

Author  Sebastian Wolf, Oliver Eiberger, Gerd Hirzinger

Video ID : 461

The DLR Hand Arm System is equipped with variable stiffness actuators (VSA). In this demonstration of robustness, the arm resists the impact of a baseball bat.

Chapter 23 — Biomimetic Robots

Kyu-Jin Cho and Robert Wood

Biomimetic robot designs attempt to translate biological principles into engineered systems, replacing more classical engineering solutions in order to achieve a function observed in the natural system. This chapter will focus on mechanism design for bio-inspired robots that replicate key principles from nature with novel engineering solutions. The challenges of biomimetic design include developing a deep understanding of the relevant natural system and translating this understanding into engineering design rules. This often entails the development of novel fabrication and actuation to realize the biomimetic design.

This chapter consists of four sections. In Sect. 23.1, we will define what biomimetic design entails, and contrast biomimetic robots with bio-inspired robots. In Sect. 23.2, we will discuss the fundamental components for developing a biomimetic robot. In Sect. 23.3, we will review detailed biomimetic designs that have been developed for canonical robot locomotion behaviors including flapping-wing flight, jumping, crawling, wall climbing, and swimming. In Sect. 23.4, we will discuss the enabling technologies for these biomimetic designs including material and fabrication.

Gravity‐independent rock‐climbing robot and a sample acquisition tool with microspine grippers

Author  Aaron Parness, Matthew Frost, Nitish Thatte, Jonathan P King, Kevin Witkoe, Moises Nevarez, Michael Garrett, Hrand Aghazarian, Brett Kennedy

Video ID : 414

NASA JPL researchers present a 250 mm diameter omni-directional anchor that uses an array of claws with suspension flexures, called microspines, designed to grip rocks on the surfaces of asteroids and comets and to grip the cliff faces and lava tubes of Mars. Part of the paper: A. Parness, M. Frost, N. Thatte, J.P. King: Gravity-independent mobility and drilling on natural rock using microspines, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), St. Paul (2012), pp. 3437-3442.

Chapter 6 — Model Identification

John Hollerbach, Wisama Khalil and Maxime Gautier

This chapter discusses how to determine the kinematic parameters and the inertial parameters of robot manipulators. Both instances of model identification are cast into a common framework of least-squares parameter estimation, and are shown to have common numerical issues relating to the identifiability of parameters, adequacy of the measurement sets, and numerical robustness. These discussions are generic to any parameter estimation problem, and can be applied in other contexts.

For kinematic calibration, the main aim is to identify the geometric Denavit–Hartenberg (DH) parameters, although joint-based parameters relating to the sensing and transmission elements can also be identified. Endpoint sensing or endpoint constraints can provide equivalent calibration equations. By casting all calibration methods as closed-loop calibration, the calibration index categorizes methods in terms of how many equations per pose are generated.

Inertial parameters may be estimated through the execution of a trajectory while sensing one or more components of force/torque at a joint. Load estimation of a handheld object is simplest because of full mobility and full wrist force-torque sensing. For link inertial parameter estimation, restricted mobility of links nearer the base as well as sensing only the joint torque means that not all inertial parameters can be identified. Those that can be identified are those that affect joint torque, although they may appear in complicated linear combinations.

Dynamic identification of a parallel robot: Trajectory with load

Author  Maxime Gautier

Video ID : 485

This video shows a trajectory with a known mass payload attached to the platform, used to identify the dynamic parameters and joint drive gains of a parallel prototype robot Orthoglyde. Details and results are given in the paper: S. Briot, M. Gautier: Global identification of joint drive gains and dynamic parameters of parallel robots, Multibody Syst. Dyn. 33(1), 3-26 (2015); doi 10.1007/s11044-013-9403-6