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Chapter 58 — Robotics in Hazardous Applications

James Trevelyan, William R. Hamel and Sung-Chul Kang

Robotics researchers have worked hard to realize a long-awaited vision: machines that can eliminate the need for people to work in hazardous environments. Chapter 60 is framed by the vision of disaster response: search and rescue robots carrying people from burning buildings or tunneling through collapsed rock falls to reach trapped miners. In this chapter we review tangible progress towards robots that perform routine work in places too dangerous for humans. Researchers still have many challenges ahead of them but there has been remarkable progress in some areas. Hazardous environments present special challenges for the accomplishment of desired tasks depending on the nature and magnitude of the hazards. Hazards may be present in the form of radiation, toxic contamination, falling objects or potential explosions. Technology that specialized engineering companies can develop and sell without active help from researchers marks the frontier of commercial feasibility. Just inside this border lie teleoperated robots for explosive ordnance disposal (EOD) and for underwater engineering work. Even with the typical tenfold disadvantage in manipulation performance imposed by the limits of today’s telepresence and teleoperation technology, in terms of human dexterity and speed, robots often can offer a more cost-effective solution. However, most routine applications in hazardous environments still lie far beyond the feasibility frontier. Fire fighting, remediating nuclear contamination, reactor decommissioning, tunneling, underwater engineering, underground mining and clearance of landmines and unexploded ordnance still present many unsolved problems.

DIGGER DTR Demining destroying anti-tank mines

Author  James P. Trevelyan

Video ID : 577

This is a Swiss-designed and built, remotely-controlled machine similar to Bozena, shown clearing vegetation. From the video, it seems to lack some of the versatility of Bozena. However, it is clearly able to continue working without being affected by powerful anti-tank mine explosions, even ones with shaped charges like the TMRP-1. Specifications include remote control, 8-ton weight, and deployment from a 20-ft standard shipping container.   The personnel protection shield provides only minimal protection. The more recent DIGGER D-3 ground-milling machine (https://www.youtube.com/watch?v=P154EDpRFew) avoids many of the weaknesses of the flail machine used in the earlier model and incorporates a more robust design, and it also has dust and shrapnel protection.

Chapter 13 — Behavior-Based Systems

François Michaud and Monica Nicolescu

Nature is filled with examples of autonomous creatures capable of dealing with the diversity, unpredictability, and rapidly changing conditions of the real world. Such creatures must make decisions and take actions based on incomplete perception, time constraints, limited knowledge about the world, cognition, reasoning and physical capabilities, in uncontrolled conditions and with very limited cues about the intent of others. Consequently, one way of evaluating intelligence is based on the creature’s ability to make the most of what it has available to handle the complexities of the real world. The main objective of this chapter is to explain behavior-based systems and their use in autonomous control problems and applications. The chapter is organized as follows. Section 13.1 overviews robot control, introducing behavior-based systems in relation to other established approaches to robot control. Section 13.2 follows by outlining the basic principles of behavior-based systems that make them distinct from other types of robot control architectures. The concept of basis behaviors, the means of modularizing behavior-based systems, is presented in Sect. 13.3. Section 13.4 describes how behaviors are used as building blocks for creating representations for use by behavior-based systems, enabling the robot to reason about the world and about itself in that world. Section 13.5 presents several different classes of learning methods for behavior-based systems, validated on single-robot and multirobot systems. Section 13.6 provides an overview of various robotics problems and application domains that have successfully been addressed or are currently being studied with behavior-based control. Finally, Sect. 13.7 concludes the chapter.

Natural interaction design of a humanoid robot

Author  François Michaud

Video ID : 418

Demonstration of the use of HBBA, hybrid behavior-based architecture, to implement three interactional capabilities on IRL-1. Reference: F. Ferland, D. Létourneau, M.-A. Legault, M. Lauria, F. Michaud: Natural interaction design of a humanoid robot, J. Human-Robot Interact. 1(2), 118-134 (2012)

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.

Aiko sidewinding

Author  Pål Liljebäck

Video ID : 254

Video of Aiko, a robot developed at the Norwegian University of Science and Technology (NTNU)/SINTEF Advanced Robotics Laboratory. In this video, the robot performs a sidewinding gait.

Chapter 43 — Telerobotics

Günter Niemeyer, Carsten Preusche, Stefano Stramigioli and Dongjun Lee

In this chapter we present an overview of the field of telerobotics with a focus on control aspects. To acknowledge some of the earliest contributions and motivations the field has provided to robotics in general, we begin with a brief historical perspective and discuss some of the challenging applications. Then, after introducing and classifying the various system architectures and control strategies, we emphasize bilateral control and force feedback. This particular area has seen intense research work in the pursuit of telepresence. We also examine some of the emerging efforts, extending telerobotic concepts to unconventional systems and applications. Finally,we suggest some further reading for a closer engagement with the field.

Multi-modal, multi-user telepresence and teleaction system

Author  M. Buss, A. Peer, T. Schauss, N. Stefanov, U. Unterhinninghofen, S. Behrendt, G. Farber, J. Leupold, K. Diepold, F. Keyrouz, M. Sarkis, P. Hinterseer, E. Steinbach, B. Farber, H. Pongrac

Video ID : 321

This video shows a multimodal, multiuser telepresence system, consisting of two teleoperated mobile manipulators, each connected to a stationary or a mobile, multimodal, human telerobotic interface. The multimodal-user feedback consists of 3-D vision, 3-D acoustic, and haptic feedback. A cooperative pipe-repair task was performed by the two teleoperated mobile manipulators. Presented at ICRA 2008.

Bilateral teleoperation of multiple quadrotors with time-varying topology

Author  Antonio Franchi, Paolo Robuffo Giordano

Video ID : 73

This video shows the bilateral teleoperation of a group of four quadrotors UAVs navigating in a cluttered environment. The human operator provides velocity-level, motion commands and receives force-feedback information on the UAV interaction with the environment (e.g., presence of obstacles, external disturbances). The coordination within the group is achieved via a fully decentralized control scheme.

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.

Pose graph compression for laser-based SLAM 3

Author  Cyrill Stachniss

Video ID : 451

This video illustrates pose graph compression, a technique for achieving long-term SLAM, as discussed in Chap.46.5, Springer Handbook of Robotics, 2nd edn (2016). Reference: H. Kretzschmar, C. Stachniss: Information-theoretic compression of pose graphs for laser-based SLAM, Int. J. Robot. Res. 31(11), 1219-1230 (2012).

Chapter 55 — Space Robotics

Kazuya Yoshida, Brian Wilcox, Gerd Hirzinger and Roberto Lampariello

In the space community, any unmanned spacecraft can be called a robotic spacecraft. However, Space Robots are considered to be more capable devices that can facilitate manipulation, assembling, or servicing functions in orbit as assistants to astronauts, or to extend the areas and abilities of exploration on remote planets as surrogates for human explorers.

In this chapter, a concise digest of the historical overview and technical advances of two distinct types of space robotic systems, orbital robots and surface robots, is provided. In particular, Sect. 55.1 describes orbital robots, and Sect. 55.2 describes surface robots. In Sect. 55.3, the mathematical modeling of the dynamics and control using reference equations are discussed. Finally, advanced topics for future space exploration missions are addressed in Sect. 55.4.

DLR ROKVISS animation

Author  Gerd Hirzinger, Klaus Landzettel

Video ID : 333

ROKVISS: animated simulation of a two-joint, torque- controlled manipulator on the ISS as it performs an iInspection task. The split screen shows simulated views of the robot (at top) and the stereo camera's view of the robot end-effector (at bottom).

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 ArmeoSpring Therapy Exoskeleton

Author  Hocoma, A.G.

Video ID : 502

The ArmeoSpring Therapy Exoskeleton is a widely-used arm- and-hand training exoskeleton manufactured by Hocoma which provides anti-gravity support and can sense trace-grasp force. It is based on the T-WREX device developed at the University of California at Irvine, which in turn was based in part of the WREX arm exoskeleton developed at the A.I. Dupont Hospital for Children.

Chapter 49 — Modeling and Control of Wheeled Mobile Robots

Claude Samson, Pascal Morin and Roland Lenain

This chaptermay be seen as a follow up to Chap. 24, devoted to the classification and modeling of basic wheeled mobile robot (WMR) structures, and a natural complement to Chap. 47, which surveys motion planning methods for WMRs. A typical output of these methods is a feasible (or admissible) reference state trajectory for a given mobile robot, and a question which then arises is how to make the physical mobile robot track this reference trajectory via the control of the actuators with which the vehicle is equipped. The object of the present chapter is to bring elements of the answer to this question based on simple and effective control strategies.

The chapter is organized as follows. Section 49.2 is devoted to the choice of controlmodels and the determination of modeling equations associated with the path-following control problem. In Sect. 49.3, the path following and trajectory stabilization problems are addressed in the simplest case when no requirement is made on the robot orientation (i. e., position control). In Sect. 49.4 the same problems are revisited for the control of both position and orientation. The previously mentionned sections consider an ideal robot satisfying the rolling-without-sliding assumption. In Sect. 49.5, we relax this assumption in order to take into account nonideal wheel-ground contact. This is especially important for field-robotics applications and the proposed results are validated through full scale experiments on natural terrain. Finally, a few complementary issues on the feedback control of mobile robots are briefly discussed in the concluding Sect. 49.6, with a list of commented references for further reading on WMRs motion control.

Tracking of arbitrary trajectories with a truck-like vehicle

Author  Pascal Morin, Claude Samson

Video ID : 182

This is an animation showing the application of the transverse function approach for the tracking of an omnidirectional frame (in blue) with a nonholonomic truck-like robot. The robot is able to maintain bounded, tracking errors in both position and orientation despite the motion of the blue frame in arbitrary directions. The animation illustrates results presented in Chap. 49.4, Springer Handbook of Robotics, 2nd edn (2016).

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.

Sensor-based online trajectory generation

Author  Torsten Kröger

Video ID : 761

The video shows the movements of a position-controlled 6-DOF industrial-robot arm equipped with a distance sensor at its end-effector. The task of the robot is to draw a rectangle on the table, while the force on the table is controlled by a force controller which acts only orthogonally to the table surface. The dimensions of the rectangle are determined by the obstacles in the robot's environment. If the obstacles are moved, the distance sensor triggers the execution of a new trajectory segment which is computed within one control cycle (1 ms), so that it can be instantly executed.