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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.

The Intelligent Autonomous Weeder

Author  Tijmen Bakker, Kees Van Asselt, Jan Bontsema, Joachim Müller, Gerrit van Straten

Video ID : 310

The Intelligent Autonomous Weeder is a four-wheel, steered, four-wheel-drive, autonomous platform which can be used for autonomous weeding operations in arable farming. An RTK DGPS system is used for navigation. The control architecture is based on a hybrid deliberative and behavior-based reactive approach.

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.

A scene of deictic interaction

Author  Takayuki Kanda

Video ID : 807

This video illustrates the "deictic interaction" in which the robot and a user interact using pointing gestures and verbal-reference terms. The robot has a capability to understand the user's deictic interaction recognizing both the pointing gesture and the reference term. In addition, there is a 'facilitation' mechanism (e.g., the robot engages in real-time joint attention), which makes the interaction smooth and natural.

Chapter 70 — Human-Robot Augmentation

Massimo Bergamasco and Hugh Herr

The development of robotic systems capable of sharing with humans the load of heavy tasks has been one of the primary objectives in robotics research. At present, in order to fulfil such an objective, a strong interest in the robotics community is collected by the so-called wearable robots, a class of robotics systems that are worn and directly controlled by the human operator. Wearable robots, together with powered orthoses that exploit robotic components and control strategies, can represent an immediate resource also for allowing humans to restore manipulation and/or walking functionalities.

The present chapter deals with wearable robotics systems capable of providing different levels of functional and/or operational augmentation to the human beings for specific functions or tasks. Prostheses, powered orthoses, and exoskeletons are described for upper limb, lower limb, and whole body structures. State-of-theart devices together with their functionalities and main components are presented for each class of wearable system. Critical design issues and open research aspects are reported.

Arm-Exos

Author  Massimo Bergamasco

Video ID : 148

The video details the Arm-Exos and, in particular, its capability for tracking the operator's motions and for rendering the contact forces in a simple, demonstrative, virtual environment.

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.

IPAnema

Author  Andreas Pott

Video ID : 50

This video demonstrates a fully constrained cable-driven parallel robot with eight cables. Reference: A. Pott, H. Mütherich, W. Kraus, V. Schmidt, P. Miermeister, A. Verl: IPAnema: A family of cable-driven parallel robots for industrial applications, Mech. Mach. Sci. 12, 119-134 (2013)

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.

Structural, inspection-path planning via iterative, viewpoint resampling with application to aerial robotics

Author  Kostas Alexis

Video ID : 604

This video presents experimental results relevant for the ICRA 2015 paper: A. Bircher, K. Alexis, M. Burri, P. Oettershagen, S. Omari, T. Mantel, R. Siegwart: Structural inspection path planning via iterative viewpoint resampling with application to aerial robotics, IEEE Int. Conf. Robot. Autom. (ICRA), Seattle (2015), pp. 6423 - 6430; doi: 10.1109/ICRA.2015.7140101

Chapter 61 — Robot Surveillance and Security

Wendell H. Chun and Nikolaos Papanikolopoulos

This chapter introduces the foundation for surveillance and security robots for multiple military and civilian applications. The key environmental domains are mobile robots for ground, aerial, surface water, and underwater applications. Surveillance literallymeans to watch fromabove,while surveillance robots are used to monitor the behavior, activities, and other changing information that are gathered for the general purpose of managing, directing, or protecting one’s assets or position. In a practical sense, the term surveillance is taken to mean the act of observation from a distance, and security robots are commonly used to protect and safeguard a location, some valuable assets, or personal against danger, damage, loss, and crime. Surveillance is a proactive operation,while security robots are a defensive operation. The construction of each type of robot is similar in nature with amobility component, sensor payload, communication system, and an operator control station.

After introducing the major robot components, this chapter focuses on the various applications. More specifically, Sect. 61.3 discusses the enabling technologies of mobile robot navigation, various payload sensors used for surveillance or security applications, target detection and tracking algorithms, and the operator’s robot control console for human–machine interface (HMI). Section 61.4 presents selected research activities relevant to surveillance and security, including automatic data processing of the payload sensors, automaticmonitoring of human activities, facial recognition, and collaborative automatic target recognition (ATR). Finally, Sect. 61.5 discusses future directions in robot surveillance and security, giving some conclusions and followed by references.

Scout robot for outdoor surveillance

Author  Nikos Papanikolopoulos

Video ID : 681

The Scout robot has been developed at the University of Minnesota in partnership with MTS, Honeywell, and ATC. The Scouts are specialized robots that carry out low-level, usually parallel tasks to meet the mission objectives. Scouts can include simple sensory units or units with locomotion, tools, or other specializations. All Scouts have a similar form factor to enable delivery of the ranger by a uniform mechanism. The Scout has a body roughly 11 cm long and 4 cm in diameter (the special foam wheels can expand to 5 cm in diameter). This body fits snugly inside a protective covering called a Sabot which absorbs much of the impact during the launch and enables the Scout to break through a glass window, land safely, and be ready to begin its mission.

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.

Generation of human-care behaviors by human-interactive robot RI-MAN

Author  Masaki Onishi, Tadashi Odashima, Shinya Hirano, Kenji Tahara, Toshiharu Mukai

Video ID : 607

This video shows the the realization of environmental interactive tasks, such as human-care tasks, by replaying the human motion repeatedly. A novel motion-generation approach is shown to integrate the cognitive information into the mimicking of human motions so as to realize the final complex task by the robot. Reference: M. Onishi, Z.W. Luo, T. Odashima, S. Hirano, K. Tahara, T. Mukai: Generation of human care behaviors by human-interactive robot RI-MAN, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), Rome (2007), pp. 3128-3129; doi: 10.1109/ROBOT.2007.363950.

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.

Visual communicative nonverbal behaviors of the Sunflower robot

Author  Kerstin Dautenhahn

Video ID : 219

The video illustrates the experiments as described in Koay et. al (2013). The Sunflower robot, developed by Kheng Lee Koay at the University of Hertfordshire, is a non-humanoid robot, using communicative signals inspired by dog-human interaction. The biological behaviors had been abstracted and translated to the specific robot embodiment. The results show that the robot is able to communicate its intention to a person and encourages the participant to attend to events and locations in a home environment. The work has been part of the of the European project LIREC (http://lirec.eu/project).

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.

Two-dimensional binary manipulator

Author  Greg Chirikjian

Video ID : 160

Greg Chirikjian's binary manipulator operating in two dimensions.

Chapter 50 — Modeling and Control of Robots on Rough Terrain

Keiji Nagatani, Genya Ishigami and Yoshito Okada

In this chapter, we introduce modeling and control for wheeled mobile robots and tracked vehicles. The target environment is rough terrains, which includes both deformable soil and heaps of rubble. Therefore, the topics are roughly divided into two categories, wheeled robots on deformable soil and tracked vehicles on heaps of rubble.

After providing an overview of this area in Sect. 50.1, a modeling method of wheeled robots on a deformable terrain is introduced in Sect. 50.2. It is based on terramechanics, which is the study focusing on the mechanical properties of natural rough terrain and its response to off-road vehicle, specifically the interaction between wheel/track and soil. In Sect. 50.3, the control of wheeled robots is introduced. A wheeled robot often experiences wheel slippage as well as its sideslip while traversing rough terrain. Therefore, the basic approach in this section is to compensate the slip via steering and driving maneuvers. In the case of navigation on heaps of rubble, tracked vehicles have much advantage. To improve traversability in such challenging environments, some tracked vehicles are equipped with subtracks, and one kinematical modeling method of tracked vehicle on rough terrain is introduced in Sect. 50.4. In addition, stability analysis of such vehicles is introduced in Sect. 50.5. Based on such kinematical model and stability analysis, a sensor-based control of tracked vehicle on rough terrain is introduced in Sect. 50.6. Sect. 50.7 summarizes this chapter.

Autonomous sub-tracks control

Author  Field Robotics Group, Tohoku University

Video ID : 190

Field Robotics Group, Tohoku University, developed an autonomous controller for the tracked vehicle (Kenaf) to generate terrain-reflective motions of the sub-tracks. Terrain information is obtained using laser range sensors that are located on both sides of the Kenaf. The videoclip shows the basic function of the controller in a simple environment.