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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.

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.

New Mexico Elementary Botball 2014 - Teagan's first-ever run.

Author  Jtlboys3

Video ID : 635

This video shows some elementary-school students running their line-following code (written in C) on a robot at the local Junior Botball Challenge event. Details from: https://www.juniorbotballchallenge.org .

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 13 — Behavior-Based Systems

François Michaud and Monica Nicolescu

Nature is filled with examples of autonomous creatures capable of dealing with the diversity, unpredictability, and rapidly changing conditions of the real world. Such creatures must make decisions and take actions based on incomplete perception, time constraints, limited knowledge about the world, cognition, reasoning and physical capabilities, in uncontrolled conditions and with very limited cues about the intent of others. Consequently, one way of evaluating intelligence is based on the creature’s ability to make the most of what it has available to handle the complexities of the real world. The main objective of this chapter is to explain behavior-based systems and their use in autonomous control problems and applications. The chapter is organized as follows. Section 13.1 overviews robot control, introducing behavior-based systems in relation to other established approaches to robot control. Section 13.2 follows by outlining the basic principles of behavior-based systems that make them distinct from other types of robot control architectures. The concept of basis behaviors, the means of modularizing behavior-based systems, is presented in Sect. 13.3. Section 13.4 describes how behaviors are used as building blocks for creating representations for use by behavior-based systems, enabling the robot to reason about the world and about itself in that world. Section 13.5 presents several different classes of learning methods for behavior-based systems, validated on single-robot and multirobot systems. Section 13.6 provides an overview of various robotics problems and application domains that have successfully been addressed or are currently being studied with behavior-based control. Finally, Sect. 13.7 concludes the chapter.

SpartacUS

Author  François Michaud

Video ID : 417

AAAI 2005 Robot Challenge entry from the Université de Sherbrooke, named Spartacus, using MBA (motivated behavioral architecture) to enable a robot to participate at the conference as a regular attendee. Reference: F. Michaud, C. Côté, D. Létourneau, Y. Brosseau, J.-M. Valin, É. Beaudry, C. Raïevsky, A. Ponchon, P. Moisan, P. Lepage, Y. Morin, F. Gagnon, P. Giguère, M.-A. Roux, S. Caron, P. Frenette, F. Kabanza: Spartacus attending the 2005 AAAI Conference, Auton. Robot. 12(2), 211–222 (2007)

Experience-based learning of high-level task representations: Demonstration (3)

Author  Monica Nicolescu

Video ID : 32

This is a video recorded in early 2000s, showing a Pioneer robot learning to traverse "gates" and move objects from a source place to a destination - the human demonstration stage. The robot execution stage is also shown in a related video in this chapter. Reference: M. Nicolescu, M.J. Mataric: Learning and interacting in human-robot domains, IEEE Trans. Syst. Man Cybernet. A31(5), 419-430 (2001)

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.

senseSoar UAV avionics testing

Author  Kostas Alexis

Video ID : 603

This video presents the avionics testing trial of the senseSoar solar-powered UAV.

Chapter 70 — Human-Robot Augmentation

Massimo Bergamasco and Hugh Herr

The development of robotic systems capable of sharing with humans the load of heavy tasks has been one of the primary objectives in robotics research. At present, in order to fulfil such an objective, a strong interest in the robotics community is collected by the so-called wearable robots, a class of robotics systems that are worn and directly controlled by the human operator. Wearable robots, together with powered orthoses that exploit robotic components and control strategies, can represent an immediate resource also for allowing humans to restore manipulation and/or walking functionalities.

The present chapter deals with wearable robotics systems capable of providing different levels of functional and/or operational augmentation to the human beings for specific functions or tasks. Prostheses, powered orthoses, and exoskeletons are described for upper limb, lower limb, and whole body structures. State-of-theart devices together with their functionalities and main components are presented for each class of wearable system. Critical design issues and open research aspects are reported.

L-Exos for upper-limb motor rehabilitation

Author  Massimo Bergamasco

Video ID : 180

The video shows the L-Exos integrated into a virtual environment, which has been specifically developed for the motor rehabilitation of the upper limb.

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.

Robotic wheelchair: Autonomous navigation with Google Glass

Author  Personal Robotics Group - OSU

Video ID : 709

For people with extreme disabilities such as ALS or quadriplegia, it is often hard to move about on their own and interact with their environments due to their immobility. Our work - nicknamed "Project Chiron" - attempts to alleviate some of this immobility with a kit that can be used on any Permobil-brand wheelchair.

Chapter 59 — Robotics in Mining

Joshua A. Marshall, Adrian Bonchis, Eduardo Nebot and Steven Scheding

This chapter presents an overview of the state of the art in mining robotics, from surface to underground applications, and beyond. Mining is the practice of extracting resources for utilitarian purposes. Today, the international business of mining is a heavily mechanized industry that exploits the use of large diesel and electric equipment. These machines must operate in harsh, dynamic, and uncertain environments such as, for example, in the high arctic, in extreme desert climates, and in deep underground tunnel networks where it can be very hot and humid. Applications of robotics in mining are broad and include robotic dozing, excavation, and haulage, robotic mapping and surveying, as well as robotic drilling and explosives handling. This chapter describes how many of these applications involve unique technical challenges for field roboticists. However, there are compelling reasons to advance the discipline of mining robotics, which include not only a desire on the part of miners to improve productivity, safety, and lower costs, but also out of a need to meet product demands by accessing orebodies situated in increasingly challenging conditions.

Autonomous loading of fragmented rock

Author  Joshua Marshall

Video ID : 718

This video shows autonomous loading of fragmented rock, first on a 1-t capacity Kubota loader at Kingston, Canada, followed by an implementation on a 14-t capacity Atlas Copco ST14 LHD in an underground mine at Kvarntorp, Sweden. The algorithm used in these demonstrations is based on force-feedback sensed in the loader cylinder pressures and utilizes an admittance control structure.

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.

A ride in the Google self-driving car

Author  Google Self-Driving Car Project

Video ID : 710

The maturity of the tools developed for mobile-robot navigation and explained in this chapter have enabled Google to integrate them into an experimental vehicle. This video demonstrates Google's self-driving technology on the road.