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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.

DART: Dense articulated real-time tracking

Author  Tanner Schmidt, Richard Newcombe, Dieter Fox

Video ID : 673

This project aims to provide a unified framework for tracking arbitrary articulated models, given their geometric and kinematic structure. Our approach uses dense input data (computing an error term on every pixel) which we are able to process in real-time by leveraging the power of GPGPU programming and very efficient representation of model geometry with signed-distance functions. This approach has proven successful on a wide variety of models including human hands, human bodies, robot arms, and articulated objects.

Chapter 80 — Roboethics: Social and Ethical Implications

Gianmarco Veruggio, Fiorella Operto and George Bekey

This chapter outlines the main developments of roboethics 9 years after a worldwide debate on the subject – that is, the applied ethics about ethical, legal, and societal aspects of robotics – opened up. Today, roboethics not only counts several thousands of voices on the Web, but is the issue of important literature relating to almost all robotics applications, and of hundreds of rich projects, workshops, and conferences. This increasing interest and sometimes even fierce debate expresses the perception and need of scientists, manufacturers, and users of professional guidelines and ethical indications about robotics in society.

Some of the issues presented in the chapter are well known to engineers, and less known or unknown to scholars of humanities, and vice versa. However, because the subject is transversal to many disciplines, complex, articulated, and often misrepresented, some of the fundamental concepts relating to ethics in science and technology are recalled and clarified.

A detailed taxonomy of sensitive areas is presented. It is based on a study of several years and referred to by scientists and scholars, the result of which is the Euron Roboethics Roadmap. This taxonomy identifies themost evident/urgent/sensitive ethical problems in the main applicative fields of robotics, leaving more in-depth research to further studies.

Roboethics: Military robotics

Author  Fiorella Operto

Video ID : 775

Ethical, legal and societal issues in military robotics. The so-called field of military robotics comprises all the devices resulting from the development of the traditional systems by robotics technology: Integrated defense systems; and A.I. systems for intelligence and surveillance controlling weapons and aircraft capabilities. Unmanned ground vehicles (UGVs), or autonomous tanks: Armored vehicles carrying weapons and/or tactical payloads, intelligent bombs and missiles. UAVs (unmanned aerial vehicles): also referred to as autonomous flying vehicles (AFVs) or drones, unmanned spy planes and remotely piloted bombers. ASV (autonomous surface vessels) and patrol boats. AUVs (autonomous underwater vehicles): Intelligent torpedoes and autonomous submarines. In this field, the main problems could arise from: inadequate management of the unstructured complexity of a hostile scenario; the unpredictability of machine behavior; the increased risk of starting a video-game-like war, due to the decreased perception of its deadly effects; unpredictable side-effects on civilian populations; human-in-control hierarchy and robot’s transparency; psychological issues of humans in robotized environments (mixed teams); accountability and responsibility gap; the assignment of liability for misbehaviors or crimes. Collateral damages: Despite the increasing success of this technology, military hierarchies feel concerned about the potential dangers. Drones can accidentally fall and possibly damage humans and objects. Daily news report about unintended injury or death of innocent non-combatants (usually known as “collateral damage”) from war theaters. Potential friendly-fire casualties in crowded battlefield or due to enemy’s tracking/hijacking.

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.

VSA-Cube arm: Drawing on a wavy surface (high stiffness)

Author  Centro di Ricerca "E. Piaggio"

Video ID : 472

A 3-DOF arm, built with VSA-cube units, performing a circle on a wavy surface with preset uniformly high stiffness.

Chapter 18 — Parallel Mechanisms

Jean-Pierre Merlet, Clément Gosselin and Tian Huang

This chapter presents an introduction to the kinematics and dynamics of parallel mechanisms, also referred to as parallel robots. As opposed to classical serial manipulators, the kinematic architecture of parallel robots includes closed-loop kinematic chains. As a consequence, their analysis differs considerably from that of their serial counterparts. This chapter aims at presenting the fundamental formulations and techniques used in their analysis.

Tripteron robot

Author  Clément Gosselin

Video ID : 54

This video demonstrates a 3-DOF decoupled translational parallel robot (Tripteron). References: 1. X. Kong, C.M. Gosselin: Kinematics and singularity analysis of a novel type of 3-CRR 3-DOF translational parallel manipulator, Inte. J. Robot. Res. 21(9), 791-798 (2002); 2. C. Gosselin: Compact dynamic models for the tripteron and quadrupteron parallel manipulators, J. Syst. Control Eng. 223(I1), 1-11 (2009)

Chapter 69 — Physical Human-Robot Interaction

Sami Haddadin and Elizabeth Croft

Over the last two decades, the foundations for physical human–robot interaction (pHRI) have evolved from successful developments in mechatronics, control, and planning, leading toward safer lightweight robot designs and interaction control schemes that advance beyond the current capacities of existing high-payload and highprecision position-controlled industrial robots. Based on their ability to sense physical interaction, render compliant behavior along the robot structure, plan motions that respect human preferences, and generate interaction plans for collaboration and coaction with humans, these novel robots have opened up novel and unforeseen application domains, and have advanced the field of human safety in robotics.

This chapter gives an overview on the state of the art in pHRI as of the date of publication. First, the advances in human safety are outlined, addressing topics in human injury analysis in robotics and safety standards for pHRI. Then, the foundations of human-friendly robot design, including the development of lightweight and intrinsically flexible force/torque-controlled machines together with the required perception abilities for interaction are introduced. Subsequently, motionplanning techniques for human environments, including the domains of biomechanically safe, risk-metric-based, human-aware planning are covered. Finally, the rather recent problem of interaction planning is summarized, including the issues of collaborative action planning, the definition of the interaction planning problem, and an introduction to robot reflexes and reactive control architecture for pHRI.

Twendy-One demo

Author  WASEDA University, Sugano Laboratory

Video ID : 623

The video shows the Twendy-One robot from the WASEDA University Sugano Laboratory performing several tasks in personal care including sitting-up motion support, transferring the care-receipient safely onto a wheelchair, or giving support during breakfast preparation. The acoustic communication between human and robot is extended by the possibility of haptic instructions.

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.

Safe human-robot cooperation

Author  Fabrizio Flacco, Torsten Kröger, Alessandro De Luca, Oussama Khatib

Video ID : 757

A real-time collision avoidance approach is presented for safe human-robot coexistence. The main contribution shown in this video is a fast method to evaluate distances between the robot and possibly moving obstacles (including humans), based on the concept of depth space. The distances are used to generate repulsive vectors that are used to control the robot while executing a generic motion task. The repulsive vectors can also take advantage of an estimation of the obstacle velocity. In order to preserve the execution of a Cartesian task with a redundant manipulator, a simple collision-avoidance algorithm has been implemented, where different reaction behaviors are set up for the end-effector and for other control points along the robot structure. Reference: F. Flacco, T. Kröger, A. De Luca, O. Khatib: A depth space approach to human-robot collision avoidance, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), Saint Paul (2012), pp. 338-345

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.

Lane tracking

Author  Alex Zelinsky

Video ID : 836

This video demonstrates robust lane tracking under variable conditions, e.g., rain and poor lighting. The system uses a particle-filter-based approach to achieve robustness.

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.

Exploitation of social cues to speed up learning

Author  Sylvain Calinon, Aude Billard

Video ID : 106

Use of social cues to speed up the imitation-learning process, with gazing and pointing information to select the objects relevant for the task. Reference: S. Calinon, A.G. Billard: Teaching a humanoid robot to recognize and reproduce social cues, Proc. IEEE Int. Symp. Robot Human Interactive Communication (Ro-Man), Hatfield (2006), pp. 346–351; URL: .

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.

Handling of a single object by multiple mobile robots based on caster-like dynamics

Author  Yasuhisa Hirata, Youhei Kume, Zhi-dong Wang, Kazuhiro Kosuge

Video ID : 193

This video focuses on how to handle a single object using the coordination actions of multiple mobile robots. Each robot is controlled based on caster dynamics. The maneuverability of the object can be changed based on the caster offset of each robot. Caster dynamics in the 3-D space is extended to the 2-D plane using a virtual 3-D caster.

Agents at play: Off-the-shelf software for practical multi-robot applications

Author  Enric Cervera, Jorge Sales, Leo Nomdedeu, Raul Marin, Veysel Gazi

Video ID : 192

This video focuses on how to use off-the-shelf components to design multirobot systems for real-world applications. The system makes use of Player and JADE as middleware, integrated using Java. The application that illustrates this system requires robots to visit destinations in an indoor environment, making use of market-based task allocation.