View Chapter

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.

Side-looking sonar system traveling down a hallway (camera view)

Author  Roman Kuc

Video ID : 314

A camera view from a mobile robot sonar traveling down a hallway past a cinder-block wall and then along the wall, passing a doorway and a window. When scanned with side-looking sonar, the door jamb and window jamb form retro-reflectors that produce echo waveforms that are distinguishable from the cinder block surface.

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 Salisbury Hand

Author  Ken Salisbury

Video ID : 751

The well-known Ken Salisbury Hand has been designed in order to optimize its workspace and its manipulation capabilities. It has been emulated in many other devices.

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.

sFly: Visual-inertial SLAM for a small helicopter in large outdoor environments

Author  Markus W. Achtelik

Video ID : 688

This video presents indicative results from the sFly project (www.sfly.org) involving fully autonomous flights with a small helicopter, performing autonomous flights in previously unknown, large outdoor spaces. The video appears in IEEE/RSJ Conference on Intelligent Robots and Systems (IROS) 2012.

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.

Explaining a typical session with Sunflower as a home companion in the Robot House

Author  Kerstin Dautenhahn

Video ID : 221

The video illustrates and explains one of the final showcases of the European project LIREC (http://lirec.eu/project) in the University of Hertfordshire Robot House. The Sunflower robot, developed at UH, provides cognitive and physical assistance in a home scenario. In the video, one of the researchers, Dag Syrdal, explains a typical session in long-term evaluation studies in the Robot House. Sunflower has access to a network of smart sensors in the Robot House. The video also illustrates the concept of migration (moving of the robot's mind/AI to a differently embodied system).

Chapter 76 — Evolutionary Robotics

Stefano Nolfi, Josh Bongard, Phil Husbands and Dario Floreano

Evolutionary Robotics is a method for automatically generating artificial brains and morphologies of autonomous robots. This approach is useful both for investigating the design space of robotic applications and for testing scientific hypotheses of biological mechanisms and processes. In this chapter we provide an overview of methods and results of Evolutionary Robotics with robots of different shapes, dimensions, and operation features. We consider both simulated and physical robots with special consideration to the transfer between the two worlds.

Evolved group coordination

Author  Phil Husbands

Video ID : 376

Identical evolved robots are required to coordinate by coming together and moving off in the same direction. No roles are pre-assigned. The robots must evolve to coordinate such that one robot takes on the role of leader and the others follow. Only minimal sensing is available (proximity IR sensing) and no dedicated communication channels. The robot neural-network controllers are evolved using a minimal simualtion and, as can be seen, these successfully transfer to reality. Work by Matt Quinn, Giles Mayley, Linc Smith and Phil Husbands at Sussex University.

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

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.

Sensor-based trajectory deformation and docking for nonholonomic mobile robots

Author  Florent Lamiraux

Video ID : 80

This video demonstrates motion planning and reactive obstacle avoidance for nonholonomic robots. A mobile robot with a trailer is asked to park into a U-shaped obstacle. Motion planning is performed by a visibility-based PRM algorithm using a flatness-based steering method built on convex combinations of canonical curves. The planned trajectory is then followed by the robot while detecting obstacles using a laser scanner. The current trajectory is locally deformed in order to avoid obstacles and to end at the detected U-shaped obstacle.

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.

DLR hand

Author  DLR -Robotics and Mechatronics Center

Video ID : 768

A DLR hand

Chapter 75 — Biologically Inspired Robotics

Fumiya Iida and Auke Jan Ijspeert

Throughout the history of robotics research, nature has been providing numerous ideas and inspirations to robotics engineers. Small insect-like robots, for example, usually make use of reflexive behaviors to avoid obstacles during locomotion, whereas large bipedal robots are designed to control complex human-like leg for climbing up and down stairs. While providing an overview of bio-inspired robotics, this chapter particularly focus on research which aims to employ robotics systems and technologies for our deeper understanding of biological systems. Unlike most of the other robotics research where researchers attempt to develop robotic applications, these types of bio-inspired robots are generally developed to test unsolved hypotheses in biological sciences. Through close collaborations between biologists and roboticists, bio-inspired robotics research contributes not only to elucidating challenging questions in nature but also to developing novel technologies for robotics applications. In this chapter, we first provide a brief historical background of this research area and then an overview of ongoing research methodologies. A few representative case studies will detail the successful instances in which robotics technologies help identifying biological hypotheses. And finally we discuss challenges and perspectives in the field.

Biologically inspired robotics (or bio-inspired robotics in short) is a very broad research area because almost all robotic systems are, in one way or the other, inspired from biological systems. Therefore, there is no clear distinction between bio-inspired robots and the others, and there is no commonly agreed definition [75.1]. For example, legged robots that walk, hop, and run are usually regarded as bio-inspired robots because many biological systems rely on legged locomotion for their survival. On the other hand, many robotics researchers implement biologicalmodels ofmotion control and navigation onto wheeled platforms, which could also be regarded as bio-inspired robots [75.2].

Salamandra Robotica II - Swimming-to-walking transition

Author  Fumiya Iida, Auke Ijspeert

Video ID : 113

This video presents the swimming-to-walking transition of a bioinspired salamander-like robot: Salamandra Robotica II. The modular configuration of this robot takes advantage of coordinated motions of motors based on the rhythmic patterns generated by CPGs. Because of the flexible coordination, the robot is able to exhibit locomotion both underwater and on the ground.

Chapter 64 — Rehabilitation and Health Care Robotics

H.F. Machiel Van der Loos, David J. Reinkensmeyer and Eugenio Guglielmelli

The field of rehabilitation robotics considers robotic systems that 1) provide therapy for persons seeking to recover their physical, social, communication, or cognitive function, and/or that 2) assist persons who have a chronic disability to accomplish activities of daily living. This chapter will discuss these two main domains and provide descriptions of the major achievements of the field over its short history and chart out the challenges to come. Specifically, after providing background information on demographics (Sect. 64.1.2) and history (Sect. 64.1.3) of the field, Sect. 64.2 describes physical therapy and exercise training robots, and Sect. 64.3 describes robotic aids for people with disabilities. Section 64.4 then presents recent advances in smart prostheses and orthoses that are related to rehabilitation robotics. Finally, Sect. 64.5 provides an overview of recent work in diagnosis and monitoring for rehabilitation as well as other health-care issues. The reader is referred to Chap. 73 for cognitive rehabilitation robotics and to Chap. 65 for robotic smart home technologies, which are often considered assistive technologies for persons with disabilities. At the conclusion of the present chapter, the reader will be familiar with the history of rehabilitation robotics and its primary accomplishments, and will understand the challenges the field may face in the future as it seeks to improve health care and the well being of persons with disabilities.

The ArmeoSpring Therapy Exoskeleton

Author  Hocoma, A.G.

Video ID : 502

The ArmeoSpring Therapy Exoskeleton is a widely-used arm- and-hand training exoskeleton manufactured by Hocoma which provides anti-gravity support and can sense trace-grasp force. It is based on the T-WREX device developed at the University of California at Irvine, which in turn was based in part of the WREX arm exoskeleton developed at the A.I. Dupont Hospital for Children.