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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.

Maccepa system

Author  Michael Gutmacher, Bram Vanderborght et al.

Video ID : 467

The Maccepa system used for a brachiation robot.

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.

Learning compliant motion from human demonstration

Author  Aude Billard

Video ID : 478

This video illustrates how one can teach a robot to display the right amount of stiffness to perform a task successfully. Decrease in stiffness is demonstrated by shaking the robot, while increase in stiffness is conveyed by pressing on the robot's arm (pressure being measured through tactile sensors along the robot's arm). Reference: K. Kronander,A. Billard: Learning compliant manipulation through kinesthetic and tactile human-robot interaction, IEEE Trans. Haptics 7(3), 367-380 (2013); doi: 10.1109/TOH.2013.54 .

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.

Controlled flight of a biologically-inspired, insect-scale robot

Author  Robert J. Wood

Video ID : 399

The Harvard Microrobotics Lab has demonstrated the first controlled flight of an insect-sized, flapping-wing robot. This video shows the 80 mg, piezoelectrically actuated robot achieving hovering flight and performing a simple lateral maneuver. Power and control signals are provided via wire tether. This work was funded by the NSF and the Wyss Institute.

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.

1961 nuclear-reactor meltdown : The SL-1 accident - United States Army Documentary - WDTVLIVE42

Author  James P. Trevelyan

Video ID : 589

This archive film, though long, provides graphic details on a relatively modest nuclear accident illustrating the difficulties that still face researchers working to provide robotic solutions.

Chapter 59 — Robotics in Mining

Joshua A. Marshall, Adrian Bonchis, Eduardo Nebot and Steven Scheding

This chapter presents an overview of the state of the art in mining robotics, from surface to underground applications, and beyond. Mining is the practice of extracting resources for utilitarian purposes. Today, the international business of mining is a heavily mechanized industry that exploits the use of large diesel and electric equipment. These machines must operate in harsh, dynamic, and uncertain environments such as, for example, in the high arctic, in extreme desert climates, and in deep underground tunnel networks where it can be very hot and humid. Applications of robotics in mining are broad and include robotic dozing, excavation, and haulage, robotic mapping and surveying, as well as robotic drilling and explosives handling. This chapter describes how many of these applications involve unique technical challenges for field roboticists. However, there are compelling reasons to advance the discipline of mining robotics, which include not only a desire on the part of miners to improve productivity, safety, and lower costs, but also out of a need to meet product demands by accessing orebodies situated in increasingly challenging conditions.

Autonomous haulage system

Author  Steven Scheding

Video ID : 145

This video shows the Autonomous Haulage System (AHS) implemented as part of Rio Tinto's Mine-of-the-Future initiative in North-Western Australia.

Chapter 56 — Robotics in Agriculture and Forestry

Marcel Bergerman, John Billingsley, John Reid and Eldert van Henten

Robotics for agriculture and forestry (A&F) represents the ultimate application of one of our society’s latest and most advanced innovations to its most ancient and important industries. Over the course of history, mechanization and automation increased crop output several orders of magnitude, enabling a geometric growth in population and an increase in quality of life across the globe. Rapid population growth and rising incomes in developing countries, however, require ever larger amounts of A&F output. This chapter addresses robotics for A&F in the form of case studies where robotics is being successfully applied to solve well-identified problems. With respect to plant crops, the focus is on the in-field or in-farm tasks necessary to guarantee a quality crop and, generally speaking, end at harvest time. In the livestock domain, the focus is on breeding and nurturing, exploiting, harvesting, and slaughtering and processing. The chapter is organized in four main sections. The first one explains the scope, in particular, what aspects of robotics for A&F are dealt with in the chapter. The second one discusses the challenges and opportunities associated with the application of robotics to A&F. The third section is the core of the chapter, presenting twenty case studies that showcase (mostly) mature applications of robotics in various agricultural and forestry domains. The case studies are not meant to be comprehensive but instead to give the reader a general overview of how robotics has been applied to A&F in the last 10 years. The fourth section concludes the chapter with a discussion on specific improvements to current technology and paths to commercialization.

Ladybird: An intelligent farm robot for the vegetable industry

Author  James Underwood, Calvin Hung, Suchet Bargoti, Mark Calleija, Robert Fitch, Juan Nieto, Salah Sukkarieh

Video ID : 305

This video showcases the Ladybird, an intelligent robot for the vegetable industry. Ladybird provides a flexible platform for sensing and automating commercial vegetable farms. The solar-electric powered vehicle has a flexible drive system that allows precise motion in potentially tight environments, and the platform geometry can be configured to suit different crop configurations. The vehicle autonomously traverses the farm, gathering data from a variety of sensors, including stereo vision, hyperspectral, thermal, and LIDAR. The data is processed to provide useful information for the management and optimization of the crop, including yield mapping, phenotyping, and disease and stress detection. Ladybird is equipped with a manipulator arm for a variety of mechanical tasks, including thinning, weeding (especially of herbicide-resistant weeds), spot spraying, foreign body removal and to support research towards automated harvesting.

Chapter 67 — Humanoids

Paul Fitzpatrick, Kensuke Harada, Charles C. Kemp, Yoshio Matsumoto, Kazuhito Yokoi and Eiichi Yoshida

Humanoid robots selectively immitate aspects of human form and behavior. Humanoids come in a variety of shapes and sizes, from complete human-size legged robots to isolated robotic heads with human-like sensing and expression. This chapter highlights significant humanoid platforms and achievements, and discusses some of the underlying goals behind this area of robotics. Humanoids tend to require the integration ofmany of the methods covered in detail within other chapters of this handbook, so this chapter focuses on distinctive aspects of humanoid robotics with liberal cross-referencing.

This chapter examines what motivates researchers to pursue humanoid robotics, and provides a taste of the evolution of this field over time. It summarizes work on legged humanoid locomotion, whole-body activities, and approaches to human–robot communication. It concludes with a brief discussion of factors that may influence the future of humanoid robots.

3-D, collision-free motion combining locomotion and manipulation by humanoid robot HRP-2

Author  Eiichi Yoshida

Video ID : 594

This video shows an example of 3-D, whole-body motion generation combining manipulation and dynamic biped locomotion, based on two-stage motion generation. At the first stage, the motion planner generates the upper-body motion with a walking path of the bounding box of the lower body. The second stage overlays the desired upper-body motion on the dynamically-stable walking motions generated by a dynamic walking-pattern generator, based on preview control of ZMP for a linear, inverted-pendulum model. If collisions occur, the planner goes back to the first stage to reshape the trajectory until collision-free motion is obtained.

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.

Gain change of the PID controller

Author  Wan Kyun Chung

Video ID : 25

The control architecture of the PID tracking controller is introduced. Moreover, according to the gain change, the performance variations of the PID controller implemented in the digital control system are shown.

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 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.

The power of prediction: Robots that read intentions

Author  E. Bicho , W. Erlhagen , E. Sousa , L. Louro , N. Hipolito , E.C. Silva , R. Silva , F. Ferreira , T. Machado , M. Hulstijn , Y.Maas , E. de Bruijn , R.H. Cuijpers , R. Newman-Norlund , H. van Schie, R.G.J. Meulenbroek , H. Bekkering

Video ID : 617

Action and intention understanding are critical components of efficient joint action. In the context of the EU Integrated Project JAST, the authors have developed an anthropomorphic robot endowed with these cognitive capacities. This project and the respective robot (ARoS) is the focus of the video. More specifically, the results illustrate crucial cognitive capacities for efficient and successful human-robot collaboration, such as goal inference, error detection, and anticipatory-action selection.