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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 teleoperation of humanoid HRP-2

Author  Sylvain Calinon, Paul Evrard, Elena Gribovskaya, Aude Billard, Abderrahmane Kheddar

Video ID : 101

Demonstration by teleoperation of the HRP-2 humanoid robot. Reference: S. Calinon, P. Evrard, E. Gribovskaya, A.G. Billard, A. Kheddar: Learning collaborative manipulation tasks by demonstration using a haptic interface, Proc. Intl Conf. Adv. Robot. (ICAR), (2009), pp. 1–6; URL: http://programming-by-demonstration.org/showVideo.php?video=10 .

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.

BONES and SUE exoskeletons for robotic therapy

Author  Julius Klein, Steve Spencer, James Allington, Marie-Helene Milot, Jim Bobrow, David Reinkensmeyer

Video ID : 498

BONES is a 5-DOF, pneumatic robot developed at the University of California at Irvine for naturalistic arm training after stroke. It incorporates an assistance-as-needed algorithm that adapts in real time to patient errors during game play by developing a computer model of the patient's weakness as a function of workspace location. The controller incorporates an anti-slacking term. SUE is a 2-DOF pneumatic robot for providing wrist assistance. The video shows a person with a stroke using the device to drive a simulated motor cycle through a simulated Death Valley.

Chapter 41 — Active Manipulation for Perception

Anna Petrovskaya and Kaijen Hsiao

This chapter covers perceptual methods in which manipulation is an integral part of perception. These methods face special challenges due to data sparsity and high costs of sensing actions. However, they can also succeed where other perceptual methods fail, for example, in poor-visibility conditions or for learning the physical properties of a scene.

The chapter focuses on specialized methods that have been developed for object localization, inference, planning, recognition, and modeling in activemanipulation approaches.We concludewith a discussion of real-life applications and directions for future research.

Tactile exploration and modeling using shape primitives

Author  Francesco Mazzini

Video ID : 76

This video shows a robot performing tactile exploration and modeling of a lab-constructed scene that was designed to be similar to those found in interventions for underwater oil spills (leaking pipe). Representing the scene with geometric primitives enables the surface to be described using only sparse tactile data from joint encoders. The robot's movements are chosen to maximize the expected increase in knowledge about the scene.

Chapter 66 — Robotics Competitions and Challenges

Daniele Nardi, Jonathan Roberts, Manuela Veloso and Luke Fletcher

This chapter explores the use of competitions to accelerate robotics research and promote science, technology, engineering, and mathematics (STEM) education. We argue that the field of robotics is particularly well suited to innovation through competitions. Two broad categories of robot competition are used to frame the discussion: human-inspired competitions and task-based challenges. Human-inspired robot competitions, of which the majority are sports contests, quickly move through platform development to focus on problemsolving and test through game play. Taskbased challenges attempt to attract participants by presenting a high aim for a robotic system. The contest can then be tuned, as required, to maintain motivation and ensure that the progress is made. Three case studies of robot competitions are presented, namely robot soccer, the UAV challenge, and the DARPA (Defense Advanced Research Projects Agency) grand challenges. The case studies serve to explore from the point of view of organizers and participants, the benefits and limitations of competitions, and what makes a good robot competition.

This chapter ends with some concluding remarks on the natural convergence of humaninspired competitions and task-based challenges in the promotion of STEM education, research, and vocations.

Brief history of RoboCup robot soccer

Author  Manuela Veloso

Video ID : 385

In this 5 min video, we explain the history of the multiple RoboCup soccer leagues.

Chapter 62 — Intelligent Vehicles

Alberto Broggi, Alex Zelinsky, Ümit Özgüner and Christian Laugier

This chapter describes the emerging robotics application field of intelligent vehicles – motor vehicles that have autonomous functions and capabilities. The chapter is organized as follows. Section 62.1 provides a motivation for why the development of intelligent vehicles is important, a brief history of the field, and the potential benefits of the technology. Section 62.2 describes the technologies that enable intelligent vehicles to sense vehicle, environment, and driver state, work with digital maps and satellite navigation, and communicate with intelligent transportation infrastructure. Section 62.3 describes the challenges and solutions associated with road scene understanding – a key capability for all intelligent vehicles. Section 62.4 describes advanced driver assistance systems, which use the robotics and sensing technologies described earlier to create new safety and convenience systems for motor vehicles, such as collision avoidance, lane keeping, and parking assistance. Section 62.5 describes driver monitoring technologies that are being developed to mitigate driver fatigue, inattention, and impairment. Section 62.6 describes fully autonomous intelligent vehicles systems that have been developed and deployed. The chapter is concluded in Sect. 62.7 with a discussion of future prospects, while Sect. 62.8 provides references to further reading and additional resources.

Bayesian Embedded Perception in Inria/Toyota instrumented platform

Author  Christian Laugier, E-Motion Team

Video ID : 566

This video illustrates the concept of “Embedded Bayesian Perception”, which has been developed by Inria and implemented on the Inria/Toyota experimental Lexus vehicle. The objective is to improve the robustness of the on-board perception system of the vehicle, by appropriately fusing the data provided by several heterogeneous sensors. The system has been developed as a key component of an electronic co-pilot, designed for the purpose of detecting dangerous driving situations a few seconds ahead. The approach relies on the concept of the “Bayesian Occupancy Filter” developed by the Inria E-Motion Team. More technical details can be found in [62.25].

Chapter 24 — Wheeled Robots

Woojin Chung and Karl Iagnemma

The purpose of this chapter is to introduce, analyze, and compare various wheeled mobile robots (WMRs) and to present several realizations and commonly encountered designs. The mobility of WMR is discussed on the basis of the kinematic constraints resulting from the pure rolling conditions at the contact points between the wheels and the ground. Practical robot structures are classified according to the number of wheels, and features are introduced focusing on commonly adopted designs. Omnimobile robot and articulated robots realizations are described. Wheel–terrain interaction models are presented in order to compute forces at the contact interface. Four possible wheel-terrain interaction cases are shown on the basis of relative stiffness of the wheel and terrain. A suspension system is required to move on uneven surfaces. Structures, dynamics, and important features of commonly used suspensions are explained.

Articulated robot - A robot pushing 3 passive trailers

Author  Woojin Chung

Video ID : 326

An omnidirectional robot pushes three passive trailers along a straight reference trajectory. There are no actuators in the modular passive trailers, and the trailers are connected through free joints. The backward-motion controller of the robot perceives the pose of the last trailer and the joint angles between trailers. Thus, one active robot can control an arbitrary number of trailers.

Chapter 65 — Domestic Robotics

Erwin Prassler, Mario E. Munich, Paolo Pirjanian and Kazuhiro Kosuge

When the first edition of this book was published domestic robots were spoken of as a dream that was slowly becoming reality. At that time, in 2008, we looked back on more than twenty years of research and development in domestic robotics, especially in cleaning robotics. Although everybody expected cleaning to be the killer app for domestic robotics in the first half of these twenty years nothing big really happened. About ten years before the first edition of this book appeared, all of a sudden things started moving. Several small, but also some larger enterprises announced that they would soon launch domestic cleaning robots. The robotics community was anxiously awaiting these first cleaning robots and so were consumers. The big burst, however, was yet to come. The price tag of those cleaning robots was far beyond what people were willing to pay for a vacuum cleaner. It took another four years until, in 2002, a small and inexpensive device, which was not even called a cleaning robot, brought the first breakthrough: Roomba. Sales of the Roomba quickly passed the first million robots and increased rapidly. While for the first years after Roomba’s release, the big players remained on the sidelines, possibly to revise their own designs and, in particular their business models and price tags, some other small players followed quickly and came out with their own products. We reported about theses devices and their creators in the first edition. Since then the momentum in the field of domestics robotics has steadily increased. Nowadays most big appliance manufacturers have domestic cleaning robots in their portfolio. We are not only seeing more and more domestic cleaning robots and lawn mowers on the market, but we are also seeing new types of domestic robots, window cleaners, plant watering robots, tele-presence robots, domestic surveillance robots, and robotic sports devices. Some of these new types of domestic robots are still prototypes or concept studies. Others have already crossed the threshold to becoming commercial products.

For the second edition of this chapter, we have decided to not only enumerate the devices that have emerged and survived in the past five years, but also to take a look back at how it all began, contrasting this retrospection with the burst of progress in the past five years in domestic cleaning robotics. We will not describe and discuss in detail every single cleaning robot that has seen the light of the day, but select those that are representative for the evolution of the technology as well as the market. We will also reserve some space for new types of mobile domestic robots, which will be the success stories or failures for the next edition of this chapter. Further we will look into nonmobile domestic robots, also called smart appliances, and examine their fate. Last but not least, we will look at the recent developments in the area of intelligent homes that surround and, at times, also control the mobile domestic robots and smart appliances described in the preceding sections.

Serbot Robot Clean Ant Profi

Author  Erwin Prassler

Video ID : 737

Video presents a professional window-leaning robot Serbot.

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 grasping

Author  Greg Chirikjian

Video ID : 162

Simulation of Greg Chirikjian's binary manipulator grasping a cylindrical object.

Chapter 27 — Micro-/Nanorobots

Bradley J. Nelson, Lixin Dong and Fumihito Arai

The field of microrobotics covers the robotic manipulation of objects with dimensions in the millimeter to micron range as well as the design and fabrication of autonomous robotic agents that fall within this size range. Nanorobotics is defined in the same way only for dimensions smaller than a micron. With the ability to position and orient objects with micron- and nanometer-scale dimensions, manipulation at each of these scales is a promising way to enable the assembly of micro- and nanosystems, including micro- and nanorobots.

This chapter overviews the state of the art of both micro- and nanorobotics, outlines scaling effects, actuation, and sensing and fabrication at these scales, and focuses on micro- and nanorobotic manipulation systems and their application in microassembly, biotechnology, and the construction and characterization of micro and nanoelectromechanical systems (MEMS/NEMS). Material science, biotechnology, and micro- and nanoelectronics will also benefit from advances in these areas of robotics.

The electromagnetic control of an untethered microrobot

Author  Bradley J. Nelson

Video ID : 12

This is a video of a computer simulation showing the electromagnetic control of an untethered microrobot for ophthalmic applications, such as targeted drug delivery and epiretinal membrane peeling.

Chapter 51 — Modeling and Control of Underwater Robots

Gianluca Antonelli, Thor I. Fossen and Dana R. Yoerger

This chapter deals with modeling and control of underwater robots. First, a brief introduction showing the constantly expanding role of marine robotics in oceanic engineering is given; this section also contains some historical backgrounds. Most of the following sections strongly overlap with the corresponding chapters presented in this handbook; hence, to avoid useless repetitions, only those aspects peculiar to the underwater environment are discussed, assuming that the reader is already familiar with concepts such as fault detection systems when discussing the corresponding underwater implementation. Themodeling section is presented by focusing on a coefficient-based approach capturing the most relevant underwater dynamic effects. Two sections dealing with the description of the sensor and the actuating systems are then given. Autonomous underwater vehicles require the implementation of mission control system as well as guidance and control algorithms. Underwater localization is also discussed. Underwater manipulation is then briefly approached. Fault detection and fault tolerance, together with the coordination control of multiple underwater vehicles, conclude the theoretical part of the chapter. Two final sections, reporting some successful applications and discussing future perspectives, conclude the chapter. The reader is referred to Chap. 25 for the design issues.

Underwater vehicle Nereus

Author  Woods Hole Oceanographic Institution

Video ID : 88

Nereus is the first vehicle to enable routine scientific investigation of the world's deepest ocean depths. Recently, Nereus successfully reached the deepest part of the world's ocean - the Challenger Deep in the Mariana Trench in the western Pacific Ocean.