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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.

Mobility prediction of rovers on soft terrain

Author  Daniel Holz, Ali Azimi, Marek Teichmann, Jozsef Kavecses

Video ID : 184

This video is an animated dynamic simulation of a vehicle traveling on sandy terrain. The simulator carefully considers mechanical interactions based on relationships between the wheel and the terrain and between the tool and the terrain. In particular, a discrete-element method is employed in order to represent the tool-sand interactions.

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.

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.

Interactive, human-robot supervision test with the long-range science rover for Mars exploration

Author  Samad Hayati, Richard Volpe, Paul Backes, J. (Bob) Balaram, Richard Welch, Robert Ivlev, Gregory Tharp, Steve Peters, Tim Ohm, Richard Petras

Video ID : 187

This video records a demonstration of the long-range rover mission on the surface of Mars. The Mars rover, the test bed Rocky 7, performs several demonstrations including 3-D terrain mapping using the panoramic camera, telescience over the internet, an autonomous mobility test, and soil sampling. This demonstration was among the preliminary tests for the Mars Pathfinder mission executed in 1997.

Chapter 64 — Rehabilitation and Health Care Robotics

H.F. Machiel Van der Loos, David J. Reinkensmeyer and Eugenio Guglielmelli

The field of rehabilitation robotics considers robotic systems that 1) provide therapy for persons seeking to recover their physical, social, communication, or cognitive function, and/or that 2) assist persons who have a chronic disability to accomplish activities of daily living. This chapter will discuss these two main domains and provide descriptions of the major achievements of the field over its short history and chart out the challenges to come. Specifically, after providing background information on demographics (Sect. 64.1.2) and history (Sect. 64.1.3) of the field, Sect. 64.2 describes physical therapy and exercise training robots, and Sect. 64.3 describes robotic aids for people with disabilities. Section 64.4 then presents recent advances in smart prostheses and orthoses that are related to rehabilitation robotics. Finally, Sect. 64.5 provides an overview of recent work in diagnosis and monitoring for rehabilitation as well as other health-care issues. The reader is referred to Chap. 73 for cognitive rehabilitation robotics and to Chap. 65 for robotic smart home technologies, which are often considered assistive technologies for persons with disabilities. At the conclusion of the present chapter, the reader will be familiar with the history of rehabilitation robotics and its primary accomplishments, and will understand the challenges the field may face in the future as it seeks to improve health care and the well being of persons with disabilities.

The WREX exoskeleton

Author  Tariq Rahman

Video ID : 499

The WREX is a spring-driven-arm exoskeleton that can provide anti-gravity support. Here, a young girl Analise puts on her WREX vest and robotic arms for the first time. Analise was born with Arthrogryposis and has been unable to move her arms and hands. Analise spent the morning being fitted for her WREX and the afternoon getting used to wearing it. Engineer Tariq Rahman and research designer Whitney Sample are the developers of the WREX (Wilmington Robotic Exoskeleton) at Alfred I. Dupon.t

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.

Cockroach-like hexapod

Author  Roger D. Quinn

Video ID : 521

A biologically inspired insect-like hexapod developed by Dr. Nelson, Dr. Bachmann, Dr. Quinn, Dr. Watson and Dr. Ritzmann.

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.

Injury evaluation of human-robot impacts

Author  Sami Haddadin, Alin Albu-Schäffer, Michael Strohmayr, Mirko Frommberger, Gerd Hirzinger

Video ID : 608

In this video, several blunt impact tests are shown, leading to an assessment of which factors dominate injury severity. We will illustrate the effects that robot speed, robot mass, and constraints in the environment have on safety in human-robot impacts. It will be shown that the intuition about high-impact loads being transmitted by heavy robots is wrong. Furthermore, the conclusion is reached that free impacts are by far less dangerous than being crushed. Reference: S. Haddadin, A. Albu-Schäffer, M. Strohmayr, M. Frommberger, G. Hirzinger: Injury evaluation of human-robot impacts, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), Pasadena (2008), pp. 2203 – 2204; doi: 10.1109/ROBOT.2008.4543534.

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.

Virtual whiskers - Highly responsive robot collision avoidance

Author  Thomas Schlegl, Torsten Kröger, Andre Gaschler, Oussama Khatib, Hubert Zangl

Video ID : 758

All mammals but humans use whiskers in order to rapidly acquire information about objects in the vicinity of the head. Collisions of the head and objects can be avoided as the contact point is moved from the body surface to the whiskers. Such a behavior is also highly desirable during many robot tasks such as for human-robot interaction. This video shows the use of novel capacitive proximity sensors so that robots can sense when they approach a human (or an object) and react before they actually collide with it. The sensors are flexible and thin so that they feature skin-like properties and can be attached to various robotic links and joint shapes. In comparison to capacitive proximity sensors, the proposed virtual whiskers offer better sensitivity towards small conductive as well as non-conductive objects. Equipped with the new proximity sensors, a seven-joint robot for human-robot interaction tasks demonstrates the efficiency and responsiveness in this video. Reference: T. Schlegl, T. Kröger, A. Gaschler, O. Khatib, H. Zangl: Virtual whiskers - Highly responsive robot collision avoidance, Proc. IEEE/RSJ Int. Conf. Intel. Robot. Syst. (IROS), Tokyo (2013)

Chapter 64 — Rehabilitation and Health Care Robotics

H.F. Machiel Van der Loos, David J. Reinkensmeyer and Eugenio Guglielmelli

The field of rehabilitation robotics considers robotic systems that 1) provide therapy for persons seeking to recover their physical, social, communication, or cognitive function, and/or that 2) assist persons who have a chronic disability to accomplish activities of daily living. This chapter will discuss these two main domains and provide descriptions of the major achievements of the field over its short history and chart out the challenges to come. Specifically, after providing background information on demographics (Sect. 64.1.2) and history (Sect. 64.1.3) of the field, Sect. 64.2 describes physical therapy and exercise training robots, and Sect. 64.3 describes robotic aids for people with disabilities. Section 64.4 then presents recent advances in smart prostheses and orthoses that are related to rehabilitation robotics. Finally, Sect. 64.5 provides an overview of recent work in diagnosis and monitoring for rehabilitation as well as other health-care issues. The reader is referred to Chap. 73 for cognitive rehabilitation robotics and to Chap. 65 for robotic smart home technologies, which are often considered assistive technologies for persons with disabilities. At the conclusion of the present chapter, the reader will be familiar with the history of rehabilitation robotics and its primary accomplishments, and will understand the challenges the field may face in the future as it seeks to improve health care and the well being of persons with disabilities.

BONES and SUE exoskeletons for robotic therapy

Author  Julius Klein, Steve Spencer, James Allington, Marie-Helene Milot, Jim Bobrow, David Reinkensmeyer

Video ID : 498

BONES is a 5-DOF, pneumatic robot developed at the University of California at Irvine for naturalistic arm training after stroke. It incorporates an assistance-as-needed algorithm that adapts in real time to patient errors during game play by developing a computer model of the patient's weakness as a function of workspace location. The controller incorporates an anti-slacking term. SUE is a 2-DOF pneumatic robot for providing wrist assistance. The video shows a person with a stroke using the device to drive a simulated motor cycle through a simulated Death Valley.

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.

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.

3-D textured model of urban environments

Author  Michael Maurer

Video ID : 269

In this video, a micro aerial vehicle developed by the Institute for Computer Graphics and Vision, Graz Univ. of Technology, flies to predefined points and captures images for building a 3-D textured model of an urban environment. The video contains a nice description of the different steps necessary to generate a precise model by fusing the areal images with public geographic data.