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Chapter 11 — Robots with Flexible Elements

Alessandro De Luca and Wayne J. Book

Design issues, dynamic modeling, trajectory planning, and feedback control problems are presented for robot manipulators having components with mechanical flexibility, either concentrated at the joints or distributed along the links. The chapter is divided accordingly into two main parts. Similarities or differences between the two types of flexibility are pointed out wherever appropriate.

For robots with flexible joints, the dynamic model is derived in detail by following a Lagrangian approach and possible simplified versions are discussed. The problem of computing the nominal torques that produce a desired robot motion is then solved. Regulation and trajectory tracking tasks are addressed by means of linear and nonlinear feedback control designs.

For robots with flexible links, relevant factors that lead to the consideration of distributed flexibility are analyzed. Dynamic models are presented, based on the treatment of flexibility through lumped elements, transfer matrices, or assumed modes. Several specific issues are then highlighted, including the selection of sensors, the model order used for control design, and the generation of effective commands that reduce or eliminate residual vibrations in rest-to-rest maneuvers. Feedback control alternatives are finally discussed.

In each of the two parts of this chapter, a section is devoted to the illustration of the original references and to further readings on the subject.

Cartesian impedance control with damping off

Author  Alin Albu-Schaeffer

Video ID : 133

This 2010 video shows the performance of a Cartesian impedance controller for the torque-controlled KUKA-LWR robot holding an extra payload, when the damping term in the controller has been turned off. The response to a contact force (a human pushing on the end-effector) is oscillatory due to the joint elasticity. This is one of two coordinated videos, the other for the case with controller damping turned on. Reference: A. Albu-Schaeffer, C. Ott, G. Hirzinger: A unified passivity-based control framework for position, torque and impedance control of flexible joint robots, Int. J. Robot. Res. 26(1), 23-39 (2007) doi: 10.1177/0278364907073776

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.

Indego

Author  Parker Hannifin

Video ID : 510

Indego is a powered orthosis developed by Vanderbilt University and commercialized by Parker Hannifin, which is designed to help individuals with paralysis to walk.

Chapter 57 — Robotics in Construction

Kamel S. Saidi, Thomas Bock and Christos Georgoulas

This chapter introduces various construction automation concepts that have been developed over the past few decades and presents examples of construction robots that are in current use (as of 2006) and/or in various stages of research and development. Section 57.1 presents an overview of the construction industry, which includes descriptions of the industry, the types of construction, and the typical construction project. The industry overview also discusses the concept of automation versus robotics in construction and breaks down the concept of robotics in construction into several levels of autonomy as well as other categories. Section 57.2 discusses some of the offsite applications of robotics in construction (such as for prefabrication), while Sect. 57.3 discusses the use of robots that perform a single task at the construction site. Section 57.4 introduces the concept of an integrated robotized construction site in which multiple robots/machines collaborate to build an entire structure. Section 57.5 discusses unsolved technical problems in construction robotics, which include interoperability, connection systems, tolerances, and power and communications. Finally, Sect. 57.6 discusses future directions in construction robotics and Sect. 57.7 gives some conclusions and suggests resources for further reading.

Obayashi ACBS (Automatic Constructions Building System)

Author  Thomas Bock

Video ID : 272

In the Obayashi ACBS (Automatic Constructions Building System) (Figure 57.29), once a story has been finished, the whole support structure, which rests on four columns, is pushed upwards by hydraulic presses to the next story over a 1.5 h period. Fully extended, the support structure is 25 m high; retracted it measures 4.5 m. Once everything has been moved up, work starts on the next story. By constructing the topmost story of the high-rise building as the roof at the beginning of the building process, the site is closed off in all directions, considerably reducing the effect of the weather and any damage it might cause.

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.

Underactuated adaptive gripper using flexural buckling

Author  Gwang-Pil Jung, Je-Sung Koh, Kyu-Jin Cho

Video ID : 409

Biologically-inspired gripper. The scalable design enables the manufacture of various sizes of the gripper. Flexure buckling provides the adaptability to grip objects of various shapes. Its differential mechanism has no wires and linkages.

RHex the parkour robot

Author  Uluc Saranli, Martin Buehler, Daniel E. Koditschek

Video ID : 400

RHex is an all-terrain walking robot that could conceivably one day climb over rubble in a rescue mission or cross the desert with environmental sensors strapped to its back. The name is pronounced "Rex" like the over-excited puppy it resembles when it is bounding over the ground; RHex is short for "robot hexapod", a name that stems from its six springy legs.

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.

PhillieBot Robot throws out the first pitch at a Phillies game

Author  Erwin Prassler

Video ID : 748

PhillieBot, developed by University of Pennsylvania, throws out the first pitch at a Phillies' baseball game (alas, in the dirt).

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.

Incremental learning of finger manipulation with tactile capability

Author  Eric Sauser, Brenna Argall, Aude Billard

Video ID : 104

Incremental learning of fingers manipulation skill, first demonstrated through a dataglove and then refined through kinesthetic teaching by exploiting the tactile capabilities of the iCub humanoid robot. Reference: E.L. Sauser, B.D. Argall, G. Metta, A.G. Billard: Iterative learning of grasp adaptation through human corrections, Robot. Auton. Syst. 60(1), 55–71 (2012); URL: http://www.sauser.org/videos.php?id=9 .

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 WREX exoskeleton

Author  Tariq Rahman

Video ID : 499

The WREX is a spring-driven-arm exoskeleton that can provide anti-gravity support. Here, a young girl Analise puts on her WREX vest and robotic arms for the first time. Analise was born with Arthrogryposis and has been unable to move her arms and hands. Analise spent the morning being fitted for her WREX and the afternoon getting used to wearing it. Engineer Tariq Rahman and research designer Whitney Sample are the developers of the WREX (Wilmington Robotic Exoskeleton) at Alfred I. Dupon.t

Chapter 46 — Simultaneous Localization and Mapping

Cyrill Stachniss, John J. Leonard and Sebastian Thrun

This chapter provides a comprehensive introduction in to the simultaneous localization and mapping problem, better known in its abbreviated form as SLAM. SLAM addresses the main perception problem of a robot navigating an unknown environment. While navigating the environment, the robot seeks to acquire a map thereof, and at the same time it wishes to localize itself using its map. The use of SLAM problems can be motivated in two different ways: one might be interested in detailed environment models, or one might seek to maintain an accurate sense of a mobile robot’s location. SLAM serves both of these purposes.

We review the three major paradigms from which many published methods for SLAM are derived: (1) the extended Kalman filter (EKF); (2) particle filtering; and (3) graph optimization. We also review recent work in three-dimensional (3-D) SLAM using visual and red green blue distance-sensors (RGB-D), and close with a discussion of open research problems in robotic mapping.

Graph-based SLAM using TORO

Author  Cyrill Stachniss

Video ID : 446

This video provides an illustration of graph-based SLAM, as described in Chap. 46.3.3, Springer Handbook of Robotics, 2nd edn (2016), using the TORO algorithm. Reference: G. Grisetti, C. Stachniss, S. Grzonka, W. Burgard. A tree parameterization for efficiently computing maximum likelihood maps using gradient descent, Proc. Robot. Sci. Syst. (RSS), Atlanta (2007)

Chapter 40 — Mobility and Manipulation

Oliver Brock, Jaeheung Park and Marc Toussaint

Mobile manipulation requires the integration of methodologies from all aspects of robotics. Instead of tackling each aspect in isolation,mobilemanipulation research exploits their interdependence to solve challenging problems. As a result, novel views of long-standing problems emerge. In this chapter, we present these emerging views in the areas of grasping, control, motion generation, learning, and perception. All of these areas must address the shared challenges of high-dimensionality, uncertainty, and task variability. The section on grasping and manipulation describes a trend towards actively leveraging contact and physical and dynamic interactions between hand, object, and environment. Research in control addresses the challenges of appropriately coupling mobility and manipulation. The field of motion generation increasingly blurs the boundaries between control and planning, leading to task-consistent motion in high-dimensional configuration spaces, even in dynamic and partially unknown environments. A key challenge of learning formobilemanipulation consists of identifying the appropriate priors, and we survey recent learning approaches to perception, grasping, motion, and manipulation. Finally, a discussion of promising methods in perception shows how concepts and methods from navigation and active perception are applied.

HERMES, a humanoid experimental robot for mobile manipulation and exploration services

Author  Rainer Bischoff

Video ID : 783

Mobile robot HERMES grasps and releases a glass with tactile sensing using joint-angle, encoder values and motor currents. The robot can fill a glass with water from a bottle using vision. It can communicate with natural spoken language,and it can come to you to get your cup and take the cup to the kitchen, by planning a path and avoiding obstacles.