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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.

Multi-robot operator control unit

Author  Bart Everett

Video ID : 701

The Space and Naval Warfare Systems Center, San Diego (SSC San Diego) has developed an unmanned vehicle and sensor operator interface capable of controlling and monitoring multiple sets of heterogeneous systems simultaneously. The modularity, scalability and flexible user interface of the multirobot operator control unit (MOCU) enable control of a wide range of vehicles and sensors in varying mission scenarios.

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.

DLR Hand Arm System: Punching holes

Author  Alin Albu-Schäffer, Thomas Bahls, Maxime Chalon, Markus Grebenstein, Oliver Eiberger, Werner Friedl, Hannes Höppner, Dominic Lakatos, Daniel Leidner, Florian Petit, Jens Reinecke, Sebastian Wolf, Tilo Wüsthoff

Video ID : 546

The DLR Hand Arm System uses a tool to punch holes into a business card. The passive flexibility in the variable stiffness actuators (VSA) helps to keep a stable grasp during the impact and protects the hardware from damage. The movement is realized by cyclic motion control and a learning algorithm to improve the accuracy of the holes.

Chapter 19 — Robot Hands

Claudio Melchiorri and Makoto Kaneko

Multifingered robot hands have a potential capability for achieving dexterous manipulation of objects by using rolling and sliding motions. This chapter addresses design, actuation, sensing and control of multifingered robot hands. From the design viewpoint, they have a strong constraint in actuator implementation due to the space limitation in each joint. After briefly introducing the overview of anthropomorphic end-effector and its dexterity in Sect. 19.1, various approaches for actuation are provided with their advantages and disadvantages in Sect. 19.2. The key classification is (1) remote actuation or build-in actuation and (2) the relationship between the number of joints and the number of actuator. In Sect. 19.3, actuators and sensors used for multifingered hands are described. In Sect. 19.4, modeling and control are introduced by considering both dynamic effects and friction. Applications and trends are given in Sect. 19.5. Finally, this chapter is closed with conclusions and further reading.

DLR hand

Author  DLR -Robotics and Mechatronics Center

Video ID : 768

A DLR hand

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.

CMU medical snake robot

Author  Howie Choset

Video ID : 175

Video of CMU medical snake robot performing a closed-chest ablation of left atrial appendage.

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 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.

Snake robot climbs a ree

Author  Cornell Wright, Austin Buchan, Ben Brown, Jason Geist, Michael Schwerin, David Rollinson, Matthew Tesch, Howie Choset

Video ID : 393

From the Biorobotics Lab at Carnegie Mellon University, a snake robot (Snakebot) demonstrates how it can climb a tree and look around. Please keep in mind that this robot climbed a specific tree with a specific trunk width to a height about 1 meter off the ground. The researchers working to design, build and program these robots still have much work to do to get these bots to climb taller trees of various sizes and to navigate over branches and wires.

Chapter 45 — World Modeling

Wolfram Burgard, Martial Hebert and Maren Bennewitz

In this chapter we describe popular ways to represent the environment of a mobile robot. For indoor environments, which are often stored using two-dimensional representations, we discuss occupancy grids, line maps, topologicalmaps, and landmark-based representations. Each of these techniques has its own advantages and disadvantages. Whilst occupancy grid maps allow for quick access and can efficiently be updated, line maps are more compact. Also landmark-basedmaps can efficiently be updated and maintained, however, they do not readily support navigation tasks such as path planning like topological representations do.

Additionally, we discuss approaches suited for outdoor terrain modeling. In outdoor environments, the flat-surface assumption underling many mapping techniques for indoor environments is no longer valid. A very popular approach in this context are elevation and variants maps, which store the surface of the terrain over a regularly spaced grid. Alternatives to such maps are point clouds, meshes, or three-dimensional grids, which provide a greater flexibility but have higher storage demands.

Learning navigation cost grids

Author  John Rebula

Video ID : 271

The video shows how the LittleDog robot of IHMC learns a terrain cost map based on several surface parameters. The map is then used for determining foot placements for the robot to enable it to traverse rough terrain.

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.

SCARA robots

Author  Adept Technology Inc

Video ID : 644

Fig. 4.20 The Adept robot uses closed-loop control and variable-reluctance motors.

Chapter 65 — Domestic Robotics

Erwin Prassler, Mario E. Munich, Paolo Pirjanian and Kazuhiro Kosuge

When the first edition of this book was published domestic robots were spoken of as a dream that was slowly becoming reality. At that time, in 2008, we looked back on more than twenty years of research and development in domestic robotics, especially in cleaning robotics. Although everybody expected cleaning to be the killer app for domestic robotics in the first half of these twenty years nothing big really happened. About ten years before the first edition of this book appeared, all of a sudden things started moving. Several small, but also some larger enterprises announced that they would soon launch domestic cleaning robots. The robotics community was anxiously awaiting these first cleaning robots and so were consumers. The big burst, however, was yet to come. The price tag of those cleaning robots was far beyond what people were willing to pay for a vacuum cleaner. It took another four years until, in 2002, a small and inexpensive device, which was not even called a cleaning robot, brought the first breakthrough: Roomba. Sales of the Roomba quickly passed the first million robots and increased rapidly. While for the first years after Roomba’s release, the big players remained on the sidelines, possibly to revise their own designs and, in particular their business models and price tags, some other small players followed quickly and came out with their own products. We reported about theses devices and their creators in the first edition. Since then the momentum in the field of domestics robotics has steadily increased. Nowadays most big appliance manufacturers have domestic cleaning robots in their portfolio. We are not only seeing more and more domestic cleaning robots and lawn mowers on the market, but we are also seeing new types of domestic robots, window cleaners, plant watering robots, tele-presence robots, domestic surveillance robots, and robotic sports devices. Some of these new types of domestic robots are still prototypes or concept studies. Others have already crossed the threshold to becoming commercial products.

For the second edition of this chapter, we have decided to not only enumerate the devices that have emerged and survived in the past five years, but also to take a look back at how it all began, contrasting this retrospection with the burst of progress in the past five years in domestic cleaning robotics. We will not describe and discuss in detail every single cleaning robot that has seen the light of the day, but select those that are representative for the evolution of the technology as well as the market. We will also reserve some space for new types of mobile domestic robots, which will be the success stories or failures for the next edition of this chapter. Further we will look into nonmobile domestic robots, also called smart appliances, and examine their fate. Last but not least, we will look at the recent developments in the area of intelligent homes that surround and, at times, also control the mobile domestic robots and smart appliances described in the preceding sections.

WINBOT W710 versus HOBOT 168 (auf Deutsch)

Author  Erwin Prassler

Video ID : 735

Video (in German) compares performance of two robotic window cleaners, namely the Winbot W710 and Hobot 168.

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.

Graph-based SLAM (Example 2)

Author  Giorgio Grisetti

Video ID : 443

This video provides an illustration of graph-based SLAM, as described in Chap. 46.3.3, Springer Handbook of Robotics, 2nd edn (2016), and performed in a parking garage in Stanford, CA.