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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.

Autonomous orchard vehicle for specialty-crop production

Author  Sanjiv Singh, Marcel Bergerman

Video ID : 91

In the United States, production of specialty crops (fruits and vegetables, tree nuts, dried fruits and horticulture and nursery crops, including floriculture) is very labor-intensive. The autonomous orchard vehicle presented in this video can be used year-round to automate tasks such as mowing, spraying, scouting for disease or insects, and estimating crop yield; or to augment humans for pruning, thinning, training trees, placing pheromone dispensers, and harvesting. Studies by the extension teams at The Pennsylvania and Washington State Universities report an increase in efficiency of up to 116% when workers perform operations on the upper part of trees onboard the vehicle, as compared to workers using ladders.

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.

Throwing a ball with the DLR VS-Joint

Author  Sebastian Wolf, Gerd Hirzinger

Video ID : 549

The video shows the difference between a stiff and a flexible actuator in a 1-DOF throwing demonstration. The variable stiffness actuator (VS-joint) can store potential energy in a strike out movement and release it by accelerating the lever and ball. Additional energy is transferred to the lever by stiffening up during the forward motion.

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 4 — Mechanism and Actuation

Victor Scheinman, J. Michael McCarthy and Jae-Bok Song

This chapter focuses on the principles that guide the design and construction of robotic systems. The kinematics equations and Jacobian of the robot characterize its range of motion and mechanical advantage, and guide the selection of its size and joint arrangement. The tasks a robot is to perform and the associated precision of its movement determine detailed features such as mechanical structure, transmission, and actuator selection. Here we discuss in detail both the mathematical tools and practical considerations that guide the design of mechanisms and actuation for a robot system.

The following sections (Sect. 4.1) discuss characteristics of the mechanisms and actuation that affect the performance of a robot. Sections 4.2–4.6 discuss the basic features of a robot manipulator and their relationship to the mathematical model that is used to characterize its performance. Sections 4.7 and 4.8 focus on the details of the structure and actuation of the robot and how they combine to yield various types of robots. The final Sect. 4.9 relates these design features to various performance metrics.

Robotic milking system

Author  Lena Rosenbohm

Video ID : 643

Fig. 4.12 DeLaval Cow Milking System features a hydraulic robot with machine-vision guided positioning.

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.

Nonverbal envelope displays to support turn-taking behavior

Author  Cynthia Breazeal

Video ID : 559

This video is a demonstration of Kismet's envelope displays to regulate turn-taking during a "conversation". In this video, Kismet is "speaking" with one person, but also acknowledges the presence of a second person. The robot is not communicating an actual language, so this video is more reminiscent of speaking with a pre-linguistic child. The nonverbal turn-taking behavior is what is being highlighted.

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.

Bimanual dissection

Author  Pierre Dupont

Video ID : 249

This 2011 video demonstrates bimanual, teleoperated tissue dissection using a CO2 laser and 1 mm-wide forceps at the Pediatric Cardiac Bioengeneering Lab at Boston Children's Hospital.

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.

Reaching in clutter with whole-arm tactile sensing

Author  Advait Jain, Marc D. Killpack, Aaron Edsinger, Charles C. Kemp

Video ID : 674

In this video, our robot Cody attempts to reach to five different goal locations using four attempts (meaning four different base locations) for each goal. For each goal, we test our single-step, quasi-static, model-predictive controller against the performance of a baseline kinematic controller that has compliance at the joints.

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.

Social learning applied to task execution

Author  Cynthia Breazeal

Video ID : 562

This is a video demonstration of the Leonardo robot integrating learning via tutelage, self motivated learning and preference learning to perform a tangram-like task. First the robot learns a policy for how to operate a remote-control box to reveal key shapes needed for the next task, integrating self-motivated exploration with tutelage. The human can shape what the robot learns through a variety of social means. Once Leo has learned a policy, the robot begins the tangram task, which is to make a sailboat figure out of the colored blocks on the virtual workspace. During this interaction, the person has a preference for which block colors to use (yellow and blue), which he conveys through nonverbal means. The robot learns this preference rule from observing these nonverbal cues. During the task, the robot needs blocks of a certain shape and color and which are not readily available on the workspace, but can be accessed by operating the remote-control box to reveal those shapes. Leo evokes those recently learned policies to access those shapes to achieve the goal of making the sailboat figure.

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.

Roller-Walker: Leg-wheel hybrid vehicle

Author  Gen Endo

Video ID : 535

A leg-wheel hybrid vehicle developed by Dr. Endo.

Chapter 30 — Sonar Sensing

Lindsay Kleeman and Roman Kuc

Sonar or ultrasonic sensing uses the propagation of acoustic energy at higher frequencies than normal hearing to extract information from the environment. This chapter presents the fundamentals and physics of sonar sensing for object localization, landmark measurement and classification in robotics applications. The source of sonar artifacts is explained and how they can be dealt with. Different ultrasonic transducer technologies are outlined with their main characteristics highlighted.

Sonar systems are described that range in sophistication from low-cost threshold-based ranging modules to multitransducer multipulse configurations with associated signal processing requirements capable of accurate range and bearing measurement, interference rejection, motion compensation, and target classification. Continuous-transmission frequency-modulated (CTFM) systems are introduced and their ability to improve target sensitivity in the presence of noise is discussed. Various sonar ring designs that provide rapid surrounding environmental coverage are described in conjunction with mapping results. Finally the chapter ends with a discussion of biomimetic sonar, which draws inspiration from animals such as bats and dolphins.

Side-looking TOF sonar simulation

Author  Roman Kuc

Video ID : 302

When a sonar is oriented 45 degrees to the side of the mobile-robot travel direction, retro-reflectors - posts and corners - produce TOF values which form a hyperbola. The hyperbola can be processed to determine the retro-reflector location.