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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)

Chapter 58 — Robotics in Hazardous Applications

James Trevelyan, William R. Hamel and Sung-Chul Kang

Robotics researchers have worked hard to realize a long-awaited vision: machines that can eliminate the need for people to work in hazardous environments. Chapter 60 is framed by the vision of disaster response: search and rescue robots carrying people from burning buildings or tunneling through collapsed rock falls to reach trapped miners. In this chapter we review tangible progress towards robots that perform routine work in places too dangerous for humans. Researchers still have many challenges ahead of them but there has been remarkable progress in some areas. Hazardous environments present special challenges for the accomplishment of desired tasks depending on the nature and magnitude of the hazards. Hazards may be present in the form of radiation, toxic contamination, falling objects or potential explosions. Technology that specialized engineering companies can develop and sell without active help from researchers marks the frontier of commercial feasibility. Just inside this border lie teleoperated robots for explosive ordnance disposal (EOD) and for underwater engineering work. Even with the typical tenfold disadvantage in manipulation performance imposed by the limits of today’s telepresence and teleoperation technology, in terms of human dexterity and speed, robots often can offer a more cost-effective solution. However, most routine applications in hazardous environments still lie far beyond the feasibility frontier. Fire fighting, remediating nuclear contamination, reactor decommissioning, tunneling, underwater engineering, underground mining and clearance of landmines and unexploded ordnance still present many unsolved problems.

Nuclear manipulator, remote-handling equipment (1960)

Author  James P. Trevelyan

Video ID : 588

Demonstration video showing the pouring of a cup of tea – illustrates the dexterity of these popular manipulators which are ubiquitous in nuclear laboratories.

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.

Synchronization and fault detection in autonomous rbots

Author  Andres Lyhne Christensen, Rehan O'Grady, Marco Dorigo

Video ID : 194

This video demonstrates a group of robots detecting faults in each other and simulating repair. The technique relies on visual fire-fly-like synchronization. Each robot synchronizes with the others based on the detection of LED lights and flashes using on-board cameras. The robots simulate fault and repair based on the frequency of flashes. The video shows an experiment with many robots working together and simulating faults and repairs.

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.

A cobot in automobile assembly

Author  Prasad Akella, Nidamaluri Nagesh, Witaya Wannasuphoprasit, J. Edward Colgate, Michael Peshkin

Video ID : 821

Collaborative robots - cobots - are a new class of robotic devices for direct physical interaction with a human operator in a shared workspace. Cobots implement software-defined "virtual surfaces" which can guide human and payload motion. A joint project of General Motors and Northwestern University has brought an alpha prototype cobot into an industrial environment. This cobot guides the removal of an automobile door from a newly painted body prior to assembly. Because of tight tolerances and curved parts, the task requires a specific escape trajectory to prevent collision of the door with the body. The cobot's virtual surfaces provide physical guidance during the critical "escape" phase, while sharing control with the human operator during other task phases. (Video Proceedings of the Int. Conf. on Robotics and Automation, 1999)

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 — Interview, February 2017

Author  Bruno Siciliano

Video ID : 846

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

Chapter 72 — Social Robotics

Cynthia Breazeal, Kerstin Dautenhahn and Takayuki Kanda

This chapter surveys some of the principal research trends in Social Robotics and its application to human–robot interaction (HRI). Social (or Sociable) robots are designed to interact with people in a natural, interpersonal manner – often to achieve positive outcomes in diverse applications such as education, health, quality of life, entertainment, communication, and tasks requiring collaborative teamwork. The long-term goal of creating social robots that are competent and capable partners for people is quite a challenging task. They will need to be able to communicate naturally with people using both verbal and nonverbal signals. They will need to engage us not only on a cognitive level, but on an emotional level as well in order to provide effective social and task-related support to people. They will need a wide range of socialcognitive skills and a theory of other minds to understand human behavior, and to be intuitively understood by people. A deep understanding of human intelligence and behavior across multiple dimensions (i. e., cognitive, affective, physical, social, etc.) is necessary in order to design robots that can successfully play a beneficial role in the daily lives of people. This requires a multidisciplinary approach where the design of social robot technologies and methodologies are informed by robotics, artificial intelligence, psychology, neuroscience, human factors, design, anthropology, and more.

Region-pointing gesture

Author  Takayuki Kanda

Video ID : 811

This short video explains what "region pointing" is. While it known that there are a variety of pointing gestures, in region pointing, unlike in other pointing gestures where the pointing arm is fixed, the arm moves as if it depicts a circle, which evokes the region it refers to.

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.

Policy refinement after demonstration

Author  Sylvain Calinon, Petar Kormushev, Darwin Caldwell

Video ID : 105

Use of stochastic optimization in the policy-parameters space to refine a skill initially learned from demonstration. Reference: S. Calinon, P. Kormushev, D.G. Caldwell: Compliant skills acquisition and multi-optima policy search with EM-based reinforcement learning, Robot. Auton. Syst. 61(4), 369–379 (2013); URL: http://vimeo.com/13387420

Chapter 76 — Evolutionary Robotics

Stefano Nolfi, Josh Bongard, Phil Husbands and Dario Floreano

Evolutionary Robotics is a method for automatically generating artificial brains and morphologies of autonomous robots. This approach is useful both for investigating the design space of robotic applications and for testing scientific hypotheses of biological mechanisms and processes. In this chapter we provide an overview of methods and results of Evolutionary Robotics with robots of different shapes, dimensions, and operation features. We consider both simulated and physical robots with special consideration to the transfer between the two worlds.

Evolution of collision-free navigation

Author  Dario Floreano

Video ID : 39

In their initial generations, robots can hardly avoid walls (one robot even approaches objects). After 50 generations, robots can navigate around the looping maze without hitting the walls.

Chapter 17 — Limbed Systems

Shuuji Kajita and Christian Ott

A limbed system is a mobile robot with a body, legs and arms. First, its general design process is discussed in Sect. 17.1. Then we consider issues of conceptual design and observe designs of various existing robots in Sect. 17.2. As an example in detail, the design of a humanoid robot HRP-4C is shown in Sect. 17.3. To design a limbed system of good performance, it is important to take into account of actuation and control, like gravity compensation, limit cycle dynamics, template models, and backdrivable actuation. These are discussed in Sect. 17.4.

In Sect. 17.5, we overview divergence of limbed systems. We see odd legged walkers, leg–wheel hybrid robots, leg–arm hybrid robots, tethered walking robots, and wall-climbing robots. To compare limbed systems of different configurations,we can use performance indices such as the gait sensitivity norm, the Froude number, and the specific resistance, etc., which are introduced in Sect. 17.6.

Biped running robot MABEL

Author  Jessy Grizzle

Video ID : 533

A biped running robot MABEL developed at the University of Michigan in the lab of Prof. Grizzle. The robot was developed in collaboration with Jonathan Hurst, Al Rizzi and Jessica Hodgins of the Robotics Institute, Carnegie Mellon University.

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.

Admittance control of a human-centered 3-DOF robotic arm using dfferential elastic actuators

Author  Marc-Antoine Legault, Marc-Antoine Lavoie, Francois Cabana, Philippe Jacob-Goudreau, Dominic Létourneau, François Michaud

Video ID : 610

This video shows the functionalities of a three-serial-DOF robotic arm where each DOF is actuated with a patent-pending differential elastic actuator (DEA). A DEA uses differential coupling between a high-impedance mechanical speed source and a low-impedance mechanical spring. A passive torsion spring (thus the name elastic), with a known impedance characteristic corresponding to the spring stiffness, is used, with an electrical DC brushless motor. A non-turning sensor connected in series with the spring measures the torque output of the actuator. Reference: M.-A. Legault, M.-A. Lavoie, F. Cabana, P. Jacob-Goudreau, D. Létourneau, F. Michaud: Admittance control of a human centered 3-DOF robotic arm using differential elastic actuators , Proc. IEEE/RSJ Int. Conf. Intel. Robot. Syst. (IROS), Nice (2008), pp. 4143–4144; doi: 10.1109/IROS.2008.4651039.