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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.

Demonstrations and reproduction of moving a chessman

Author  Sylvain Calinon, Florent Guenter, Aude Billard

Video ID : 97

A robot learns how to make a chess move from multiple demonstrations and to reproduce the skill in a new situation (different position of the chessman) by finding a controller which satisfies both the task constraints (what-to-imitate) and constraints relative to its body limitation (how-to-imitate). Reference: S. Calinon, F. Guenter, A. Billard: On earning, representing and generalizing a task in a humanoid robot, IEEE Trans. Syst. Man Cybernet. B 37(2), 286-298 (2007); URL:

Chapter 54 — Industrial Robotics

Martin Hägele, Klas Nilsson, J. Norberto Pires and Rainer Bischoff

Much of the technology that makes robots reliable, human friendly, and adaptable for numerous applications has emerged from manufacturers of industrial robots. With an estimated installation base in 2014 of about 1:5million units, some 171 000 new installations in that year and an annual turnover of the robotics industry estimated to be US$ 32 billion, industrial robots are by far the largest commercial application of robotics technology today.

The foundations for robot motion planning and control were initially developed with industrial applications in mind. These applications deserve special attention in order to understand the origin of robotics science and to appreciate the many unsolved problems that still prevent the wider use of robots in today’s agile manufacturing environments. In this chapter, we present a brief history and descriptions of typical industrial robotics applications and at the same time we address current critical state-of-the-art technological developments. We show how robots with differentmechanisms fit different applications and how applications are further enabled by latest technologies, often adopted from technological fields outside manufacturing automation.

We will first present a brief historical introduction to industrial robotics with a selection of contemporary application examples which at the same time refer to a critical key technology. Then, the basic principles that are used in industrial robotics and a review of programming methods will be presented. We will also introduce the topic of system integration particularly from a data integration point of view. The chapter will be closed with an outlook based on a presentation of some unsolved problems that currently inhibit wider use of industrial robots.

SMErobot D4 "The woodworking assistant"

Author  Martin Haegele

Video ID : 266

Video of demonstrator D4 of SMErobot - The European Robot Initiative for Strengthening the Competitiveness of SMEs in Manufacturing: "The woodworking assistant / Der Schreinerei-Assistent" SMErobot was an Integrated Project within the 6th Framework Programme of the EC to create a new family of SME-suitable robots and to exploit its potentials for competitive SME manufacturing (March 2005 - May 2009). For more details on the project and this welding robot, please also watch the "SMErobot video Coffee Break (English)" with Video ID: 261 as well as the "SMErobot Final Project Video" with Video ID: 262 or visit the respective demonstrator website:

Chapter 24 — Wheeled Robots

Woojin Chung and Karl Iagnemma

The purpose of this chapter is to introduce, analyze, and compare various wheeled mobile robots (WMRs) and to present several realizations and commonly encountered designs. The mobility of WMR is discussed on the basis of the kinematic constraints resulting from the pure rolling conditions at the contact points between the wheels and the ground. Practical robot structures are classified according to the number of wheels, and features are introduced focusing on commonly adopted designs. Omnimobile robot and articulated robots realizations are described. Wheel–terrain interaction models are presented in order to compute forces at the contact interface. Four possible wheel-terrain interaction cases are shown on the basis of relative stiffness of the wheel and terrain. A suspension system is required to move on uneven surfaces. Structures, dynamics, and important features of commonly used suspensions are explained.

An omnidirectional robot with four mecanum wheels

Author  Nexus Automation Limited

Video ID : 327

This video shows a holonomic omnidirectional mobile robot with four mecanum wheels. The mecanum wheel is similar to the Swedish wheel. The rollers of the mecanum wheel have an axis of rotation at 45° to the axis of the wheel hub rotation. The design problem of omnidirectional robots becomes easier because the rotating axes of all wheel hubs can be placed in parallel.

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.

Torque control for teaching peg-in-hole via physical human-robot interaction

Author  Alin-Albu Schäffer

Video ID : 627

Teaching by demonstration is a typical application for impedance controllers. A practical demonstration was given with the task of teaching for automatic insertion of a piston into a motor block. Teaching is realized by guiding the robot with the human hand. It was initially known that the axes of the holes in the motor block were vertically oriented. In the teaching phase, high stiffness components for the orientations were commanded (150 Nm/rad), while the translational stiffness was set to zero. This allowed only translational movements to be demonstrated by the human operator. In the second phase, the taught trajectory has been automatically reproduced by the robot. In this phase, high values were assigned for the translational stiffness (3000 N/m), while the stiffness for the rotations was low (60 Nm/rad). This enabled the robot to compensate for the remaining position errors. For two pistons, the total time for the assembly was 6 s. In this experiment, the assembly was executed automatically four-times faster than by the human operator holding the robot as an input device in the teaching phase (24 s), while the free-hand execution of the task by a human requires about 4 s.

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.

6-DOF statically balanced parallel robot

Author  Clément Gosselin

Video ID : 48

This video demonstrates a 6-DOF statically balanced parallel robot. References: 1. C. Gosselin, J. Wang, T. Laliberté, I. Ebert-Uphoff: On the design of a statically balanced 6-DOF parallel manipulator, Proc. IFToMM Tenth World Congress Theory of Machines and Mechanisms, Oulu (1999) pp. 1045-1050; 2. C. Gosselin, J. Wang: On the design of statically balanced motion bases for flight simulators, Proc. AIAA Modeling and Simulation Technologies Conf., Boston (1998), pp. 272-282; 3. I. Ebert-Uphoff, C. Gosselin: Dynamic modeling of a class of spatial statically-balanced parallel platform mechanisms, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), Detroit (1999), Vol. 2, pp. 881-888

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.

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

Author  Kazuhiro Kosuge

Video ID : 785

When multiple robots are utilized for the handling of an object, the slippage between wheels and the ground is the most serious challenge for coordinating the multiple robots. A control algorithm has been developed for mobile robots, which assumes they each possess caster-like dynamics.

Chapter 7 — Motion Planning

Lydia E. Kavraki and Steven M. LaValle

This chapter first provides a formulation of the geometric path planning problem in Sect. 7.2 and then introduces sampling-based planning in Sect. 7.3. Sampling-based planners are general techniques applicable to a wide set of problems and have been successful in dealing with hard planning instances. For specific, often simpler, planning instances, alternative approaches exist and are presented in Sect. 7.4. These approaches provide theoretical guarantees and for simple planning instances they outperform samplingbased planners. Section 7.5 considers problems that involve differential constraints, while Sect. 7.6 overviews several other extensions of the basic problem formulation and proposed solutions. Finally, Sect. 7.8 addresses some important andmore advanced topics related to motion planning.

Motion planning in multi-robot scenario.

Author  Jamie Snape, Jur van den Berg, Stephen J. Guy, Dinesh Manocha

Video ID : 22

Motion planning can be used for multiple robot scenarios. In this video, each iRobot Roomba senses its surroundings and acts independently without central coordination or communication with other robots. This approach uses the current position and the velocity of other robots to predict their future trajectories in order to avoid collisions.

Chapter 63 — Medical Robotics and Computer-Integrated Surgery

Russell H. Taylor, Arianna Menciassi, Gabor Fichtinger, Paolo Fiorini and Paolo Dario

The growth of medical robotics since the mid- 1980s has been striking. From a few initial efforts in stereotactic brain surgery, orthopaedics, endoscopic surgery, microsurgery, and other areas, the field has expanded to include commercially marketed, clinically deployed systems, and a robust and exponentially expanding research community. This chapter will discuss some major themes and illustrate them with examples from current and past research. Further reading providing a more comprehensive review of this rapidly expanding field is suggested in Sect. 63.4.

Medical robotsmay be classified in many ways: by manipulator design (e.g., kinematics, actuation); by level of autonomy (e.g., preprogrammed versus teleoperation versus constrained cooperative control), by targeted anatomy or technique (e.g., cardiac, intravascular, percutaneous, laparoscopic, microsurgical); or intended operating environment (e.g., in-scanner, conventional operating room). In this chapter, we have chosen to focus on the role of medical robots within the context of larger computer-integrated systems including presurgical planning, intraoperative execution, and postoperative assessment and follow-up.

First, we introduce basic concepts of computerintegrated surgery, discuss critical factors affecting the eventual deployment and acceptance of medical robots, and introduce the basic system paradigms of surgical computer-assisted planning, execution, monitoring, and assessment (surgical CAD/CAM) and surgical assistance. In subsequent sections, we provide an overview of the technology ofmedical robot systems and discuss examples of our basic system paradigms, with brief additional discussion topics of remote telesurgery and robotic surgical simulators. We conclude with some thoughts on future research directions and provide suggested further reading.

Robot for single-port surgery by the University of Nebraska

Author  University of Nebraska Medical Center

Video ID : 827

Robot for single-port surgery by the University of Nebraska: The video includes an explanation of the working principle, tests, and comments by clinicians.

Chapter 44 — Networked Robots

Dezhen Song, Ken Goldberg and Nak-Young Chong

As of 2013, almost all robots have access to computer networks that offer extensive computing, memory, and other resources that can dramatically improve performance. The underlying enabling framework is the focus of this chapter: networked robots. Networked robots trace their origin to telerobots or remotely controlled robots. Telerobots are widely used to explore undersea terrains and outer space, to defuse bombs and to clean up hazardous waste. Until 1994, telerobots were accessible only to trained and trusted experts through dedicated communication channels. This chapter will describe relevant network technology, the history of networked robots as it evolves from teleoperation to cloud robotics, properties of networked robots, how to build a networked robot, example systems. Later in the chapter, we focus on the recent progress on cloud robotics, and topics for future research.

A multi-operator, multi-robot teleoperation system

Author  Nak Young Chong

Video ID : 84

A multi-operator, multi-robot teleoperation system for collaborative maintenance operations: Video Proc. of ICRA 2001. Over the past decades, problems and notable results have been reported mainly in the single-operator single-robot (SOSR) teleoperation system. Recently, the need for cooperation has rapidly emerged in many possible applications such as plant maintenance, construction, and surgery, and considerable efforts have therefore been made toward the coordinated control of multi-operator, multi-robot (MOMR) teleoperation. We have developed coordinated control technologies for multi-telerobot cooperation in a common environment remotely controlled from multiple operators physically distant from each other. To overcome the operators' delayed visual perception arising from network throughput limitations, we have suggested several coordinated control aids at the local operator site. Operators control their master to get their telerobot to cooperate with the counterpart telerobot using the predictive simulator, as well as video image feedback. This video explains the details of the testbed and investigates the use of an online predictive simulator to assist the operator in coping with time delay.

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.

Aiko sidewinding

Author  Pål Liljebäck

Video ID : 254

Video of Aiko, a robot developed at the Norwegian University of Science and Technology (NTNU)/SINTEF Advanced Robotics Laboratory. In this video, the robot performs a sidewinding gait.