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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.

Safe physical human-robot collaboration

Author  Fabrizio Flacco, Alessandro De Luca

Video ID : 609

The video summarizes the state of the on-going research activities on physical human-robot collaboration (pHRC) at the DIAG Robotics Lab, Sapienza University of Rome, as of March 2013, and performed within the European Research Project FP7 287511 SAPHARI (http://www.saphari.eu) Reference: F. Flacco, A. De Luca: Safe physical human-robot collaboration, IEEE/RSJ Int. Conf. Intel. Robot. Syst. (IROS), Tokyo (2013)

Generation of human-care behaviors by human-interactive robot RI-MAN

Author  Masaki Onishi, Tadashi Odashima, Shinya Hirano, Kenji Tahara, Toshiharu Mukai

Video ID : 607

This video shows the the realization of environmental interactive tasks, such as human-care tasks, by replaying the human motion repeatedly. A novel motion-generation approach is shown to integrate the cognitive information into the mimicking of human motions so as to realize the final complex task by the robot. Reference: M. Onishi, Z.W. Luo, T. Odashima, S. Hirano, K. Tahara, T. Mukai: Generation of human care behaviors by human-interactive robot RI-MAN, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), Rome (2007), pp. 3128-3129; doi: 10.1109/ROBOT.2007.363950.

Chapter 43 — Telerobotics

Günter Niemeyer, Carsten Preusche, Stefano Stramigioli and Dongjun Lee

In this chapter we present an overview of the field of telerobotics with a focus on control aspects. To acknowledge some of the earliest contributions and motivations the field has provided to robotics in general, we begin with a brief historical perspective and discuss some of the challenging applications. Then, after introducing and classifying the various system architectures and control strategies, we emphasize bilateral control and force feedback. This particular area has seen intense research work in the pursuit of telepresence. We also examine some of the emerging efforts, extending telerobotic concepts to unconventional systems and applications. Finally,we suggest some further reading for a closer engagement with the field.

Single- and dual-arm supervisory and shared control

Author  Paul S. Schenker, Antal K. Bejczy, Won S. Kim

Video ID : 299

This video shows single- and dual-arm supervisory and shared teleoperation control for the remote repair of solar panels attached to a space satellite.

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.

Experience-based learning of high-level task representations: Demonstration

Author  Monica Nicolescu

Video ID : 27

This is a video recorded in early 2000s, showing a Pioneer robot learning to visit a number of targets in a certain order - the human demonstration stage. The robot execution stage is also shown in a related video in this chapter. References: 1. M. Nicolescu, M.J. Mataric: Experience-based learning of task representations from human-robot interaction, Proc. IEEE Int. Symp. Comput. Intell. Robot. Autom. Banff (2001), pp. 463-468; 2. M. Nicolescu, M.J. Mataric: Learning and interacting in human-robot domains, IEEE Trans. Syst. Man Cybernet. A31(5), 419-430 (2001)

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 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.

Active compliant insertion

Author  Nabil Simaan

Video ID : 244

Shows rapid deployment of a continuum robot inside a tube using force sensing at the backbones and a generalization of the compliant motion controller initially presented in [1]. This experiment is associated with [2] which is not published. The algorithms have been validated successfully on two cadavers as reported in Hamlyn 2013 paper and in a TBME paper currently under review [1] R. E. Goldman, A. Bajo, N. Simaan: Compliant motion control for continuum robots with intrinsic actuation sensing, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), Shanghai (2011), pp. 1126-1132; [2] R. E. Goldman, A. Bajo, N. Simaan: Compliant motion control for multi-segment continuum robots with actuation force sensing, IEEE Trans. Robot. (2013), submitted

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: Introduction

Author  Fiorella Operto

Video ID : 773

Introduction ton Ethical, Legal and Societal issues. This is the first time in history that humanity is nearing the achievement of replicating an intelligent and autonomous entity. This compels the scientific community to examine closely the very concept of intelligence – in humans and animals, and of the me- chanical – from a cybernetic standpoint. In fact, complex concepts like autonomy, learning, consciousness, evaluation, free will, decision making, freedom, emotions, and many others need to be analyzed, taking into account that the same concept may not have, in humans, animals, and machines, the same semantic meaning. From this standpoint, it can be seen as natural and necessary that robotics draws on several other disciplines, such as logic, linguistics, neuroscience, psychology, biology, physiology, philosophy, litera- ture, natural history, anthropology, art, and design. In fact, robotics de facto combines the so-called two cultural spheres, science and humanities. The effort to design roboethics should take into account this specificity. This means that experts will consider robotics as a whole - in spite of the current early stage which recalls a melting pot – so they can achieve the vision of robotics’ future. “Roboethics is an applied ethics whose objective is to develop scientific/cultural/technical tools that can be shared by different social groups and beliefs. These tools aim to promote and encourage the development of robotics for the advancement of human society and individuals, and to help preventing its misuse against humankind.” (Veruggio, 2002)

Chapter 43 — Telerobotics

Günter Niemeyer, Carsten Preusche, Stefano Stramigioli and Dongjun Lee

In this chapter we present an overview of the field of telerobotics with a focus on control aspects. To acknowledge some of the earliest contributions and motivations the field has provided to robotics in general, we begin with a brief historical perspective and discuss some of the challenging applications. Then, after introducing and classifying the various system architectures and control strategies, we emphasize bilateral control and force feedback. This particular area has seen intense research work in the pursuit of telepresence. We also examine some of the emerging efforts, extending telerobotic concepts to unconventional systems and applications. Finally,we suggest some further reading for a closer engagement with the field.

Semi-autonomous teleoperation of multiple UAVs: Passing a narrow gap

Author  Antonio Franchi, Paolo Robuffo Giordano

Video ID : 71

This video shows the bilateral teleoperation of a group of four quadrotors UAVs navigating in a cluttered environment. The human operator provides velocity-level motion commands and receives force-feedback information on the UAV interaction with the environment (e.g., presence of obstacles and external disturbances).

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.

Autonomous robot cars drive in the DARPA Urban Challenge

Author  GovernmentTechnology

Video ID : 714

In order to forster research and development in the domain of autonomous navigation, the DARPA agency organized a challenge in 2007 for competitors to develop autonomous vehicles which are able to follow an itinerary through an urban environment. Navigation within unstructured areas like parking lots made extensive use of RRT-like methods.

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.

Combined mobility and manipulation - Operational space control of free-flying space robots

Author  Jeff Russakow, Stephen Rock

Video ID : 787

An environmental space is simulated in two dimensions using an air-bearing over a flat surface. The operational space-control framework enables the dynamically decoupled motion and force control of the object.