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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 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.

CLASH: Climbing loose vertical cloth

Author  Paul Birkmeyer, Andrew G. Gillies, Ronald S. Fearing

Video ID : 391

CLASH is a 10 cm, 15 g robot capable of climbing vertical loose-cloth surfaces at 15 cm/s. The robot has a single actuator driving its six legs which are equipped with novel passive foot mechanisms to facilitate smooth engagement and disengagement of spines. Descended from the DASH hexapedal robot, CLASH features a redesigned transmission with a lower profile and improved dynamics for climbing.

Chapter 15 — Robot Learning

Jan Peters, Daniel D. Lee, Jens Kober, Duy Nguyen-Tuong, J. Andrew Bagnell and Stefan Schaal

Machine learning offers to robotics a framework and set of tools for the design of sophisticated and hard-to-engineer behaviors; conversely, the challenges of robotic problems provide both inspiration, impact, and validation for developments in robot learning. The relationship between disciplines has sufficient promise to be likened to that between physics and mathematics. In this chapter, we attempt to strengthen the links between the two research communities by providing a survey of work in robot learning for learning control and behavior generation in robots. We highlight both key challenges in robot learning as well as notable successes. We discuss how contributions tamed the complexity of the domain and study the role of algorithms, representations, and prior knowledge in achieving these successes. As a result, a particular focus of our chapter lies on model learning for control and robot reinforcement learning. We demonstrate how machine learning approaches may be profitably applied, and we note throughout open questions and the tremendous potential for future research.

Machine learning table tennis

Author  Jan Peters, Katharina Mülling, Jens Kober, Oliver Kroemer, Zhikun Wang

Video ID : 354

The video shows recent successful demonstrations of using machine learning for robot table tennis. The first part shows learning of motor primitives for forehand strikes by training a robot with a mixture of imitation and reinforcement learning. The second part shows how the robot can anticipate an opponent's intended targets based on both forehand and backhand primitives. The video illustrates Sect. 15.3.5 Policy Search of the Springer Handbook of Robotics, 2nd edn (2016). Reference: K. Mülling, J. Kober, O. Kroemer, J. Peters: Learning to select and generalize striking movements in robot table tennis, Int. J. Robot. Res. 32(3), 263-279 (2013)

Chapter 8 — Motion Control

Wan Kyun Chung, Li-Chen Fu and Torsten Kröger

This chapter will focus on the motion control of robotic rigid manipulators. In other words, this chapter does not treat themotion control ofmobile robots, flexible manipulators, and manipulators with elastic joints. The main challenge in the motion control problem of rigid manipulators is the complexity of their dynamics and uncertainties. The former results from nonlinearity and coupling in the robot manipulators. The latter is twofold: structured and unstructured. Structured uncertainty means imprecise knowledge of the dynamic parameters and will be touched upon in this chapter, whereas unstructured uncertainty results from joint and link flexibility, actuator dynamics, friction, sensor noise, and unknown environment dynamics, and will be treated in other chapters. In this chapter, we begin with an introduction to motion control of robot manipulators from a fundamental viewpoint, followed by a survey and brief review of the relevant advanced materials. Specifically, the dynamic model and useful properties of robot manipulators are recalled in Sect. 8.1. The joint and operational space control approaches, two different viewpoints on control of robot manipulators, are compared in Sect. 8.2. Independent joint control and proportional– integral–derivative (PID) control, widely adopted in the field of industrial robots, are presented in Sects. 8.3 and 8.4, respectively. Tracking control, based on feedback linearization, is introduced in Sect. 8.5. The computed-torque control and its variants are described in Sect. 8.6. Adaptive control is introduced in Sect. 8.7 to solve the problem of structural uncertainty, whereas the optimality and robustness issues are covered in Sect. 8.8. To compute suitable set point signals as input values for these motion controllers, Sect. 8.9 introduces reference trajectory planning concepts. Since most controllers of robotmanipulators are implemented by using microprocessors, the issues of digital implementation are discussed in Sect. 8.10. Finally, learning control, one popular approach to intelligent control, is illustrated in Sect. 8.11.

Virtual whiskers - Highly responsive robot collision avoidance

Author  Thomas Schlegl, Torsten Kröger, Andre Gaschler, Oussama Khatib, Hubert Zangl

Video ID : 758

All mammals but humans use whiskers in order to rapidly acquire information about objects in the vicinity of the head. Collisions of the head and objects can be avoided as the contact point is moved from the body surface to the whiskers. Such a behavior is also highly desirable during many robot tasks such as for human-robot interaction. This video shows the use of novel capacitive proximity sensors so that robots can sense when they approach a human (or an object) and react before they actually collide with it. The sensors are flexible and thin so that they feature skin-like properties and can be attached to various robotic links and joint shapes. In comparison to capacitive proximity sensors, the proposed virtual whiskers offer better sensitivity towards small conductive as well as non-conductive objects. Equipped with the new proximity sensors, a seven-joint robot for human-robot interaction tasks demonstrates the efficiency and responsiveness in this video. Reference: T. Schlegl, T. Kröger, A. Gaschler, O. Khatib, H. Zangl: Virtual whiskers - Highly responsive robot collision avoidance, Proc. IEEE/RSJ Int. Conf. Intel. Robot. Syst. (IROS), Tokyo (2013)

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.

Swarm robot system

Author  James McLurkin

Video ID : 215

This video captures the interactions in a robot system developed at MIT, illustrating several swarm behaviors. These behaviors include dispersing, clumping, and following-the-leader.

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 38 — Grasping

Domenico Prattichizzo and Jeffrey C. Trinkle

This chapter introduces fundamental models of grasp analysis. The overall model is a coupling of models that define contact behavior with widely used models of rigid-body kinematics and dynamics. The contact model essentially boils down to the selection of components of contact force and moment that are transmitted through each contact. Mathematical properties of the complete model naturally give rise to five primary grasp types whose physical interpretations provide insight for grasp and manipulation planning.

After introducing the basic models and types of grasps, this chapter focuses on the most important grasp characteristic: complete restraint. A grasp with complete restraint prevents loss of contact and thus is very secure. Two primary restraint properties are form closure and force closure. A form closure grasp guarantees maintenance of contact as long as the links of the hand and the object are well-approximated as rigid and as long as the joint actuators are sufficiently strong. As will be seen, the primary difference between form closure and force closure grasps is the latter’s reliance on contact friction. This translates into requiring fewer contacts to achieve force closure than form closure.

The goal of this chapter is to give a thorough understanding of the all-important grasp properties of form and force closure. This will be done through detailed derivations of grasp models and discussions of illustrative examples. For an indepth historical perspective and a treasure-trove bibliography of papers addressing a wide range of topics in grasping, the reader is referred to [38.1].

Grasp analysis using the MATLAB toolbox SynGrasp

Author  Monica Malvezzi, Guido Gioioso, Gionata Salvietti, Domenico Prattichizzo

Video ID : 551

In this video a examples of few grasp analysis are documented and reported. The analysis is performed using SynGrasp, a MATLAB toolbox for grasp analysis. It provides a graphical user interface (GUI) which the user can adopt to easily load a hand and an object, and a series of functions that the user can assemble and modify to exploit all the toolbox features. The video shows how to use SynGrasp to model and analyze grasping, and, in particular it shows how users can select and load in the GUI a hand model, then choose an object and place it in the workspace selecting its position w.r.t. the hand. The grasp is obtained closing the hand from an initial configuration, which can be set by the users acting on hand joints. Once the grasp is defined, it can be analyzed by evaluating grasp quality measures available in the toolbox. Grasps can be described either using the provided grasp planner or directly defining contact points on the hand with the respective contact normal directions. SynGrasp can model both fully and underactuated robotic hands. An important role in grasp analysis, in particular with underactuated hands, is played by system compliance. SynGrasp can model the stiffness at contact points, at the joints or in the actuation system including transmission. A wide set of analytical functions, continuously increasing with new features and capabilities, has been developed to investigate the main grasp properties: controllable forces and object displacement, manipulability analysis, grasp stiffness and different measures of grasp quality. A set of functions for the graphical representation of the hand, the object, and the main analysis results is provided. The toolbox is freely available at http://syngrasp.dii.unisi.it.

Chapter 10 — Redundant Robots

Stefano Chiaverini, Giuseppe Oriolo and Anthony A. Maciejewski

This chapter focuses on redundancy resolution schemes, i. e., the techniques for exploiting the redundant degrees of freedom in the solution of the inverse kinematics problem. This is obviously an issue of major relevance for motion planning and control purposes.

In particular, task-oriented kinematics and the basic methods for its inversion at the velocity (first-order differential) level are first recalled, with a discussion of the main techniques for handling kinematic singularities. Next, different firstorder methods to solve kinematic redundancy are arranged in two main categories, namely those based on the optimization of suitable performance criteria and those relying on the augmentation of the task space. Redundancy resolution methods at the acceleration (second-order differential) level are then considered in order to take into account dynamics issues, e.g., torque minimization. Conditions under which a cyclic task motion results in a cyclic joint motion are also discussed; this is a major issue when a redundant manipulator is used to execute a repetitive task, e.g., in industrial applications. The use of kinematic redundancy for fault tolerance is analyzed in detail. Suggestions for further reading are given in a final section.

KUKA LBR iiwa - Kinematic Redundancy

Author  KUKA Roboter GmbH

Video ID : 813

The video shows the robot dexterity achieved by kinematic redundancy and illustrates the basic concept of self-motion (here called null-space motion).

Chapter 0 — Preface

Bruno Siciliano, Oussama Khatib and Torsten Kröger

The preface of the Second Edition of the Springer Handbook of Robotics contains three videos about the creation of the book and using its multimedia app on mobile devices.

Bruno Siciliano — Keynote, February 2017

Author  Bruno Siciliano

Video ID : 847

Bruno Siciliano, Editor of the Springer Handbook of Robotics, gives a keynote during the One SpringerNature event in Barcelona on 7 February 2017.

Chapter 56 — Robotics in Agriculture and Forestry

Marcel Bergerman, John Billingsley, John Reid and Eldert van Henten

Robotics for agriculture and forestry (A&F) represents the ultimate application of one of our society’s latest and most advanced innovations to its most ancient and important industries. Over the course of history, mechanization and automation increased crop output several orders of magnitude, enabling a geometric growth in population and an increase in quality of life across the globe. Rapid population growth and rising incomes in developing countries, however, require ever larger amounts of A&F output. This chapter addresses robotics for A&F in the form of case studies where robotics is being successfully applied to solve well-identified problems. With respect to plant crops, the focus is on the in-field or in-farm tasks necessary to guarantee a quality crop and, generally speaking, end at harvest time. In the livestock domain, the focus is on breeding and nurturing, exploiting, harvesting, and slaughtering and processing. The chapter is organized in four main sections. The first one explains the scope, in particular, what aspects of robotics for A&F are dealt with in the chapter. The second one discusses the challenges and opportunities associated with the application of robotics to A&F. The third section is the core of the chapter, presenting twenty case studies that showcase (mostly) mature applications of robotics in various agricultural and forestry domains. The case studies are not meant to be comprehensive but instead to give the reader a general overview of how robotics has been applied to A&F in the last 10 years. The fourth section concludes the chapter with a discussion on specific improvements to current technology and paths to commercialization.

VisualGPS – High accuracy localization for forestry machinery

Author  Juergen Rossmann, Michael Schluse, Arno Buecken, Christian Schlette, Markus Emde

Video ID : 96

Developments in space robotics continue to find their way into our everyday lives. These advances, for instance, include novel methods to increase localization accuracy in determining one's position in comparison to conventional GPS systems. The example here is the "VisualGPS" approach that helps to estimate the position of forestry machinery, such as harvesters in the woods, with high accuracy. For "VisualGPS", harvesters are equipped with laser scanners. The sensors scan the surrounding area to generate landmarks from the tree positions. The tree positions are combined into a local, single-tree map. By comparing the local, single-tree map with a map generated from aerial survey data, the current machine position can be calculated with an accuracy of 0.5 m.