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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.

SMErobotics project video

Author  Martin Haegele, Thilo Zimmermann, Björn Kahl

Video ID : 260

SMErobotics: Europe's leading robot manufacturers and research institutes have teamed up with the European Robotics Initiative for Strengthening the Competitiveness of SMEs in Manufacturing - to make the vision of cognitive robotics a reality in a key segment of EU manufacturing. Funded by the European Union 7th Framework Programme under GA number 287787. Project runtime: 01.01.2012 - 30.06.2016 About this video: Chapter 1: Introduction (0:00); Chapter 2: SME Requirements (00:28); Chapter 3: First Teaching Steps (00:49); Chapter 4: Setup and Calibration (01:25); Chapter 5: Benefits of Skills (01:58); Chapter 6: Skill-based Teaching (02:40); Chapter 7: Teaching Methods (03:23); Chapter 8: Use of CAD Data (03:49); Chapter 9: Automatic program generation (04:27); Chapter 10: What if (05:07); Chapter 11: Exception Handling (05:40); Chapter 12: Total Cost of Ownership - Intro (06:16); Chapter 13: Total Cost of Ownership & Summary (06:55); Chapter 14: Conclusion (07:45); Chapter 15: The Consortium (08:21); http://www.smerobotics.org/project/project_video.html

Chapter 63 — Medical Robotics and Computer-Integrated Surgery

Russell H. Taylor, Arianna Menciassi, Gabor Fichtinger, Paolo Fiorini and Paolo Dario

The growth of medical robotics since the mid- 1980s has been striking. From a few initial efforts in stereotactic brain surgery, orthopaedics, endoscopic surgery, microsurgery, and other areas, the field has expanded to include commercially marketed, clinically deployed systems, and a robust and exponentially expanding research community. This chapter will discuss some major themes and illustrate them with examples from current and past research. Further reading providing a more comprehensive review of this rapidly expanding field is suggested in Sect. 63.4.

Medical robotsmay be classified in many ways: by manipulator design (e.g., kinematics, actuation); by level of autonomy (e.g., preprogrammed versus teleoperation versus constrained cooperative control), by targeted anatomy or technique (e.g., cardiac, intravascular, percutaneous, laparoscopic, microsurgical); or intended operating environment (e.g., in-scanner, conventional operating room). In this chapter, we have chosen to focus on the role of medical robots within the context of larger computer-integrated systems including presurgical planning, intraoperative execution, and postoperative assessment and follow-up.

First, we introduce basic concepts of computerintegrated surgery, discuss critical factors affecting the eventual deployment and acceptance of medical robots, and introduce the basic system paradigms of surgical computer-assisted planning, execution, monitoring, and assessment (surgical CAD/CAM) and surgical assistance. In subsequent sections, we provide an overview of the technology ofmedical robot systems and discuss examples of our basic system paradigms, with brief additional discussion topics of remote telesurgery and robotic surgical simulators. We conclude with some thoughts on future research directions and provide suggested further reading.

Da Vinci surgery on a grape

Author  Edward Hospital, Naperville, Illinois

Video ID : 823

The movie shows the peeling of a grape by using the robotic tools of the Da Vinci robot: Precision, dexterity and motion scaling are impressive.

Chapter 62 — Intelligent Vehicles

Alberto Broggi, Alex Zelinsky, Ümit Özgüner and Christian Laugier

This chapter describes the emerging robotics application field of intelligent vehicles – motor vehicles that have autonomous functions and capabilities. The chapter is organized as follows. Section 62.1 provides a motivation for why the development of intelligent vehicles is important, a brief history of the field, and the potential benefits of the technology. Section 62.2 describes the technologies that enable intelligent vehicles to sense vehicle, environment, and driver state, work with digital maps and satellite navigation, and communicate with intelligent transportation infrastructure. Section 62.3 describes the challenges and solutions associated with road scene understanding – a key capability for all intelligent vehicles. Section 62.4 describes advanced driver assistance systems, which use the robotics and sensing technologies described earlier to create new safety and convenience systems for motor vehicles, such as collision avoidance, lane keeping, and parking assistance. Section 62.5 describes driver monitoring technologies that are being developed to mitigate driver fatigue, inattention, and impairment. Section 62.6 describes fully autonomous intelligent vehicles systems that have been developed and deployed. The chapter is concluded in Sect. 62.7 with a discussion of future prospects, while Sect. 62.8 provides references to further reading and additional resources.

Motion prediction using the Bayesian-occupancy-filter approach (Inria)

Author  Christian Laugier, E-Motion Team

Video ID : 420

This video illustrates the prediction capabilities of the Bayesian-occupancy-filter approach which is able to maintain an updated record and estimate of the relatives positions and velocities of an autonomous vehicle and of a detected-and-tracked moving obstacle (e.g., a pedestrian in the video). The approach still works despite temporary obstructions. The method has been patented in, and commercialized since, 2005. More details in [62.60].

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.

Binary-manipulator object recovery

Author  Greg Chirikjian

Video ID : 164

Video of Greg Chirikjian's binary manipulator performing an object retrieval task for satellite-recovery applications.

Chapter 25 — Underwater Robots

Hyun-Taek Choi and Junku Yuh

Covering about two-thirds of the earth, the ocean is an enormous system that dominates processes on the Earth and has abundant living and nonliving resources, such as fish and subsea gas and oil. Therefore, it has a great effect on our lives on land, and the importance of the ocean for the future existence of all human beings cannot be overemphasized. However, we have not been able to explore the full depths of the ocean and do not fully understand the complex processes of the ocean. Having said that, underwater robots including remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs) have received much attention since they can be an effective tool to explore the ocean and efficiently utilize the ocean resources. This chapter focuses on design issues of underwater robots including major subsystems such as mechanical systems, power sources, actuators and sensors, computers and communications, software architecture, and manipulators while Chap. 51 covers modeling and control of underwater robots.

Preliminary experimental result of an AUV yShark2

Author  Hyun-Taek Choi

Video ID : 799

This video shows preliminary experimental result of an underwater robot named yShark2 developed by KRISO (Korea Research Institute of Ships and Ocean Engineering). yShark is a test platform and is designed especially for testing the intelligent algorithms we are working on. For this, it has AHRS, IMU, DVL, two cameras, an LED light, a depth sensor, eight-channel ranging sonar as basic navigation sensors, and we can install an imaging sonar DIDSON for obtaining pictures as shown in Fig. 25.2. More importantly, its system software architecture is implemented using the structure explained in Fig. 25.7. The motion in this video is controlled by autonomous algorithms.

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.

PETMAN tests Camo

Author  Boston Dynamics

Video ID : 457

The PETMAN robot was developed by Boston Dynamics with funding from the DoD CBD program. It is used to test the performance of protective clothing designed for hazardous environments. The video shows initial testing in a chemical protection suit and gas mask. PETMAN has sensors embedded in its skin that detect any chemicals leaking through the suit. The skin also maintains a microclimate inside the clothing by sweating and regulating temperature. Partners in developing PETMAN were MRIGlobal, Measurement Technology Northwest, Smith Carter, SRD, CUH2A, and HHI.

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.

ACM-R5H

Author  Shigeo Hirose

Video ID : 397

The ACM-R5H is a snake robot that can go where no human can go. It is designed to perform underwater inspections and search-and-rescue missions in hazardous environments. It is a snake-like robot with extra dust sealing, waterproofing and a rigid structure that allows operation under any severe condition. It is composed of several modules with small passive wheels that allow the robot to move smoothly on surfaces. ACM-R5 can also move sinuously in underwater environments. In the front unit, a wireless camera is mounted on a special mechanism that keeps the view orientation always horizontal. ACM-R5H is ideal for inspection and search operations in underwater environments.

Chapter 14 — AI Reasoning Methods for Robotics

Michael Beetz, Raja Chatila, Joachim Hertzberg and Federico Pecora

Artificial intelligence (AI) reasoning technology involving, e.g., inference, planning, and learning, has a track record with a healthy number of successful applications. So can it be used as a toolbox of methods for autonomous mobile robots? Not necessarily, as reasoning on a mobile robot about its dynamic, partially known environment may differ substantially from that in knowledge-based pure software systems, where most of the named successes have been registered. Moreover, recent knowledge about the robot’s environment cannot be given a priori, but needs to be updated from sensor data, involving challenging problems of symbol grounding and knowledge base change. This chapter sketches the main roboticsrelevant topics of symbol-based AI reasoning. Basic methods of knowledge representation and inference are described in general, covering both logicand probability-based approaches. The chapter first gives a motivation by example, to what extent symbolic reasoning has the potential of helping robots perform in the first place. Then (Sect. 14.2), we sketch the landscape of representation languages available for the endeavor. After that (Sect. 14.3), we present approaches and results for several types of practical, robotics-related reasoning tasks, with an emphasis on temporal and spatial reasoning. Plan-based robot control is described in some more detail in Sect. 14.4. Section 14.5 concludes.

From knowledge grounding to dialogue processing

Author  Séverin Lemaignan, Rachid Alami

Video ID : 705

This 2012 video documents the entire process of perspective-aware knowledge acquisition, knowledge representation and storage, and dialogue understanding. It demonstrates several examples of the natural interaction of a human with a PR2 robot, including speech recognition and action execution.

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.

A path-following control scheme for a four-wheeled mobile robot

Author  Genya Ishigami, Keiji Nagatani, Kazuya Yoshida

Video ID : 188

This video shows a feedback control for planetary rovers. It calculates both steering and driving maneuvers that can compensate for wheel slips and also enable the rover to successfully traverse a sandy slope. The performance was confirmed in slope traversal experiments using a four-wheeled rover test bed. In this split video clip, no slip control is performed on the left, and slip-compensation-feedback control is conducted on the right. The rover's motion is detected by the visual odometry system using a telecentric camera.

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.

Overview of Autom: A robotic health coach for weight management

Author  Cynthia Breazeal

Video ID : 558

This video presents an overview of Autom, a robot designed to serve as a personal coach for weight management during a longitudinal study. Fifteen robots were deployed over a period of two months and were compared to two other conditions: A computer coach with the same dialog (but no physical or social embodiment) and a paper log (standard of care). The primary question the study addressed was long-term usage and engagement as that is the most critical to keeping weight off. The hypothesis (verified by the longitudinal study) is that the physical-social embodiment makes a positive difference in people's sustained engagement, perception of their working alliance, and social support provided by the robot (than the other two interventions). People were more engaged with the robot than the other two interventions, and the emotional bond was notable in the robot modality and much less so in the other two interventions.