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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.

Dancing with Juliet

Author  Oussama Khatib, Kyong-Sok Chang, Oliver Brock, Kazuhito Yokoi, Arancha Casal, Robert Holmberg

Video ID : 820

This video presents experiments in human-robot interaction using the Stanford Mobile Manipulator platforms. Each platform consists of a Puma 560 manipulator mounted on a holonomic mobile base. The experiments shown in this video are the results of the implementation of various methodologies developed for establishing the basic autonomous capabilities needed for robot operations in human environments. The integration of mobility and manipulation is based on a task-oriented control strategy which provides the user with two basic control primitives: end-effector task control and platform self-posture control.

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 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.

Human robot arm with redundancy resolution

Author  PRISMA Lab

Video ID : 816

In this video, the mapping of human-arm motion to an anthropomorphic robot arm (7-DOF Kuka LWR ) using Xsens MVN is demonstrated. The desired end-effector trajectories of the robot are reconstructed from the human hand, forearm and upper arm trajectories in the Cartesian space obtained from the motion tracking system by means of human-arm biomechanical models and sensor-fusion algorithms embedded in the Xsens technology. The desired pose of the robot is reconstructed taking into account the differences between the robot and human-arm kinematics and is obtained by suitably scaling to the human-arm link dimensions.

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.

Demonstration by kinesthetic teaching

Author  Baris Akgun, Maya Cakmak, Karl Jiang, Andrea Thomaz

Video ID : 100

Demonstration by kinesthetic teaching with the Simon humanoid robot. Reference: B. Akgun, M. Cakmak, K. Jiang, A.L. Thomaz: Keyframe-based learning from demonstration, Int. J. Social Robot. 4(4), 343–355 (2012); URL: https://www.youtube.com/user/SimonTheSocialRobot .

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.

Biologically-inspired climbing with a hexapedal robot

Author  Matthew J. Spenko, Galen C. Haynes, Jeffrey A. Saunders, Mark R. Cutkosky, Alfred A. Rizzi, Robert J. Full, Daniel E. Koditschek

Video ID : 390

A climbing robot that grasps the microtexture of the surface using special feet and special motions. The development team includes researchers from U Penn, Stanford, Berkeley, Carnegie Mellon and Boston Dynamics.

Chapter 26 — Flying Robots

Stefan Leutenegger, Christoph Hürzeler, Amanda K. Stowers, Kostas Alexis, Markus W. Achtelik, David Lentink, Paul Y. Oh and Roland Siegwart

Unmanned aircraft systems (UASs) have drawn increasing attention recently, owing to advancements in related research, technology, and applications. While having been deployed successfully in military scenarios for decades, civil use cases have lately been tackled by the robotics research community.

This chapter overviews the core elements of this highly interdisciplinary field; the reader is guided through the design process of aerial robots for various applications starting with a qualitative characterization of different types of UAS. Design and modeling are closely related, forming a typically iterative process of drafting and analyzing the related properties. Therefore, we overview aerodynamics and dynamics, as well as their application to fixed-wing, rotary-wing, and flapping-wing UAS, including related analytical tools and practical guidelines. Respecting use-case-specific requirements and core autonomous robot demands, we finally provide guidelines to related system integration challenges.

UAV stabilization, mapping and obstacle avoidance using VI-Sensor

Author  Skybotix AG

Video ID : 689

The video depicts UAV stabilization, mapping and obstacle avoidance using the Skybotix--Autonomous Systems Lab VI-Sensor - on-board and realtime. The robot is enabled with assisted teleoperation without line of sight and without the use of GPS during the ICARUS trials in Marche-En-Famenne.

Chapter 51 — Modeling and Control of Underwater Robots

Gianluca Antonelli, Thor I. Fossen and Dana R. Yoerger

This chapter deals with modeling and control of underwater robots. First, a brief introduction showing the constantly expanding role of marine robotics in oceanic engineering is given; this section also contains some historical backgrounds. Most of the following sections strongly overlap with the corresponding chapters presented in this handbook; hence, to avoid useless repetitions, only those aspects peculiar to the underwater environment are discussed, assuming that the reader is already familiar with concepts such as fault detection systems when discussing the corresponding underwater implementation. Themodeling section is presented by focusing on a coefficient-based approach capturing the most relevant underwater dynamic effects. Two sections dealing with the description of the sensor and the actuating systems are then given. Autonomous underwater vehicles require the implementation of mission control system as well as guidance and control algorithms. Underwater localization is also discussed. Underwater manipulation is then briefly approached. Fault detection and fault tolerance, together with the coordination control of multiple underwater vehicles, conclude the theoretical part of the chapter. Two final sections, reporting some successful applications and discussing future perspectives, conclude the chapter. The reader is referred to Chap. 25 for the design issues.

Underwater vehicle Nereus

Author  Woods Hole Oceanographic Institution

Video ID : 88

Nereus is the first vehicle to enable routine scientific investigation of the world's deepest ocean depths. Recently, Nereus successfully reached the deepest part of the world's ocean - the Challenger Deep in the Mariana Trench in the western Pacific Ocean.

Chapter 46 — Simultaneous Localization and Mapping

Cyrill Stachniss, John J. Leonard and Sebastian Thrun

This chapter provides a comprehensive introduction in to the simultaneous localization and mapping problem, better known in its abbreviated form as SLAM. SLAM addresses the main perception problem of a robot navigating an unknown environment. While navigating the environment, the robot seeks to acquire a map thereof, and at the same time it wishes to localize itself using its map. The use of SLAM problems can be motivated in two different ways: one might be interested in detailed environment models, or one might seek to maintain an accurate sense of a mobile robot’s location. SLAM serves both of these purposes.

We review the three major paradigms from which many published methods for SLAM are derived: (1) the extended Kalman filter (EKF); (2) particle filtering; and (3) graph optimization. We also review recent work in three-dimensional (3-D) SLAM using visual and red green blue distance-sensors (RGB-D), and close with a discussion of open research problems in robotic mapping.

Treemap: An O(log n) algorithm for indoor simultaneous localization and mapping

Author  Udo Frese

Video ID : 441

This video provides an illustration of graph-based SLAM, described in Chap. 46.3.3, Springer Handbook of Robotics, 2nd edn (2016). Reference: U. Frese: Treemap: An O(log n) algorithm for indoor simultaneous localization and mapping, Auton. Robot. 21(2), 103–122 (2006).

Chapter 36 — Motion for Manipulation Tasks

James Kuffner and Jing Xiao

This chapter serves as an introduction to Part D by giving an overview of motion generation and control strategies in the context of robotic manipulation tasks. Automatic control ranging from the abstract, high-level task specification down to fine-grained feedback at the task interface are considered. Some of the important issues include modeling of the interfaces between the robot and the environment at the different time scales of motion and incorporating sensing and feedback. Manipulation planning is introduced as an extension to the basic motion planning problem, which can be modeled as a hybrid system of continuous configuration spaces arising from the act of grasping and moving parts in the environment. The important example of assembly motion is discussed through the analysis of contact states and compliant motion control. Finally, methods aimed at integrating global planning with state feedback control are summarized.

Mesoscale manipulation: System, modeling, planning and control

Author  David J. Cappelleri et al.

Video ID : 359

This video shows an example of peg-in-hole manipulation on the mesoscale. Three robust motion primitives are introduced, i.e., one-point sticking contact with counterclockwise rotation, two-point contact motion without rotation, and robust rotation. These motion primitives are sequentially executed to accomplish the peg-in-hole manipulation task.

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 video coffee break

Author  Martin Haegele

Video ID : 261

Coffee break: Tom and Michael, two stressed workers of an SME, dream of a robot helping them in their daily routine. One idea inspires the next ... until their ruminations advance to novel work environments and new and different types of robots, topics to be explored in the final project. © Copyright This video is copyrighted property of the SMErobot consortium. Any use of the video other than for private, non-commercial viewing purposes is strictly prohibited. http://www.smerobot.org/