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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.

Dynamic multicontact motion

Author  Eiichi Yoshida

Video ID : 597

A method to plan optimal whole-body, dynamic motion in multicontact non-gaited transitions has been developed. Using a B-spline time parameterization for the active joints, we turn the motion-planning problem into a semi-infinite programming formulation which is solved by nonlinear optimization techniques. We address the problem of the balance within the optimization problem and demonstrate that generating whole-body multicontact dynamic motion for complex tasks is possible.

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.

AwAS - II: Actuator with adjustable stiffness

Author  Nikolaos Tsagarakis, Darwin Caldwell et al.

Video ID : 699

Actuator with adjustable stiffness(AwAS-II) - variable stiffness and position behavior.

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 43 — Telerobotics

Günter Niemeyer, Carsten Preusche, Stefano Stramigioli and Dongjun Lee

In this chapter we present an overview of the field of telerobotics with a focus on control aspects. To acknowledge some of the earliest contributions and motivations the field has provided to robotics in general, we begin with a brief historical perspective and discuss some of the challenging applications. Then, after introducing and classifying the various system architectures and control strategies, we emphasize bilateral control and force feedback. This particular area has seen intense research work in the pursuit of telepresence. We also examine some of the emerging efforts, extending telerobotic concepts to unconventional systems and applications. Finally,we suggest some further reading for a closer engagement with the field.

Passivity of IPC strategy at 30-Hz sample rate

Author  Stefano Stramigioli

Video ID : 724

In this short video, the effectiveness of the passive sampling approach and IPC control are shown. A "PD" like control is implemented digitally in the classical way and also using IPC and passive sampling. At the used sampling frequency of 30 Hz, it is shown that instability occurs for the standard implementation, but is completely absent in the proposed way.

Chapter 79 — Robotics for Education

David P. Miller and Illah Nourbakhsh

Educational robotics programs have become popular in most developed countries and are becoming more and more prevalent in the developing world as well. Robotics is used to teach problem solving, programming, design, physics, math and even music and art to students at all levels of their education. This chapter provides an overview of some of the major robotics programs along with the robot platforms and the programming environments commonly used. Like robot systems used in research, there is a constant development and upgrade of hardware and software – so this chapter provides a snapshot of the technologies being used at this time. The chapter concludes with a review of the assessment strategies that can be used to determine if a particular robotics program is benefitting students in the intended ways.

Autonomous aerial-vehicle, carrier-landing contest (2001)

Author  KIPR

Video ID : 633

KIPR's first aerial robot contest featuring several middle and high schools from Oklahoma and neighboring states. It was held at the University of Oklahoma's Rawl Engineering Practice Facility. Teams used AR drones and KIPR's CBC2 controller to program the drone and have the drone react autonomously. No human control was used. Four very different approaches are shown to the event, in which the teams programmed their robots to totry land on a moving platform.

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.

Kineassist

Author  Discover Channel/Michael Peshkin

Video ID : 505

The Kineassist is a gait-training robot which rolls behind a patient and compliantly supports the trunk and pelvis. It enables patients to challenge the limits of their stability, catching them if they fall.

Lokomat

Author  Hocoma, A.G.

Video ID : 503

The Lokomat was one of the first robotic gait-training devices and is now one of the most widely-used robotic therapy devices.

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.

Coevolved predator and prey robots

Author  Dario Floreano

Video ID : 38

Coevolved predator and prey robots engaged in a tournament. The predator and prey robot (from left to right) are placed in an arena surrounded by walls and are allowed to interact for several trials starting at different, randomly-generated orientations. Predators are selected on the basis of the percentage of trials in which they are able to catch (i.e., to touch) the prey, and prey on the basis of the percentage of trials in which they were able to escape (i.e., to not be touched by) predators. Predators have a vision system, whereas the prey have only short-range distance sensors, but can go twice as fast as the predator. Collision between robots is detected by a conductive belt at the base of the robots.

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].

JenaWalker - Biped robot with biologically-inspired, bi-articular springs

Author  Fumiya Iida, Auke Ijspeertb

Video ID : 110

This video presents dynamic locomotion of a passivity-based, biped robot which contains biologically inspired bi-articular springs. The platform was developed for the purpose of understanding the roles of diverse muscle groups in human legs. A set of mechanical tension springs was incorporated to simulate muscles including bi-articular muscles which span two joints.

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.

MARS (multiple autonomous robots)

Author  Camillo J. Taylor, Vijay Kumar

Video ID : 204

The goal of the research is to develop a framework and the support tools for the deployment of multiple autonomous robots in an unstructured and unknown environment, with applications to reconnaissance, surveillance, target acquisition, and the removal of explosive ordnance. The current state of the art in control software enables supervised autonomy, a paradigm in which a human user can command and control one robot using teleoperation and close supervisory control. The objective here is to develop the software framework and tools for a new generation of autonomous robots.