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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.

Experience-based learning of high-level task representations: Demonstration (2)

Author  Monica Nicolescu

Video ID : 30

This is a video recorded in early 2000s, showing a Pioneer robot learning to slalom around a number of targets in a certain order - the human demonstration stage. The robot execution stage is also shown in a related video in this chapter. References: 1. M. Nicolescu, M.J. Mataric: Experience-based learning of task representations from human-robot interaction, Proc. IEEE Int. Symp. Comput. Intell. Robot. Autom. , Banff (2001), pp. 463-468; 2. M. Nicolescu, M.J. Mataric: Learning and interacting in human-robot domains, IEEE Trans. Syst. Man Cybernet. A31(5), 419-430 (2001)

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 0 — Preface

Bruno Siciliano, Oussama Khatib and Torsten Kröger

The preface of the Second Edition of the Springer Handbook of Robotics contains three videos about the creation of the book and using its multimedia app on mobile devices.

The handbook — A short story

Author  Oussama Khatib

Video ID : 844

With a bit of humor, this video illustrates how the first edition of the Springer Handbook of Robotics was created.

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.

Bayesian Embedded Perception in Inria/Toyota instrumented platform

Author  Christian Laugier, E-Motion Team

Video ID : 566

This video illustrates the concept of “Embedded Bayesian Perception”, which has been developed by Inria and implemented on the Inria/Toyota experimental Lexus vehicle. The objective is to improve the robustness of the on-board perception system of the vehicle, by appropriately fusing the data provided by several heterogeneous sensors. The system has been developed as a key component of an electronic co-pilot, designed for the purpose of detecting dangerous driving situations a few seconds ahead. The approach relies on the concept of the “Bayesian Occupancy Filter” developed by the Inria E-Motion Team. More technical details can be found in [62.25].

Chapter 40 — Mobility and Manipulation

Oliver Brock, Jaeheung Park and Marc Toussaint

Mobile manipulation requires the integration of methodologies from all aspects of robotics. Instead of tackling each aspect in isolation,mobilemanipulation research exploits their interdependence to solve challenging problems. As a result, novel views of long-standing problems emerge. In this chapter, we present these emerging views in the areas of grasping, control, motion generation, learning, and perception. All of these areas must address the shared challenges of high-dimensionality, uncertainty, and task variability. The section on grasping and manipulation describes a trend towards actively leveraging contact and physical and dynamic interactions between hand, object, and environment. Research in control addresses the challenges of appropriately coupling mobility and manipulation. The field of motion generation increasingly blurs the boundaries between control and planning, leading to task-consistent motion in high-dimensional configuration spaces, even in dynamic and partially unknown environments. A key challenge of learning formobilemanipulation consists of identifying the appropriate priors, and we survey recent learning approaches to perception, grasping, motion, and manipulation. Finally, a discussion of promising methods in perception shows how concepts and methods from navigation and active perception are applied.

Rolling Justin - a platform for mobile manipulation

Author  DLR

Video ID : 786

Rolling Justin is a four-wheeled, mobile manipulator, which is a research platform that enables implementation and demonstration of sophisticated control algorithms and dexterous manipulation.

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.

A single-motor-actuated, miniature, steerable jumping robot

Author  Jianguo Zhao, Jing Xu, Bingtuan Gao, Ning Xi, Fernando J. Cintron, Matt W. Mutka, Li Xiao

Video ID : 280

The contents of the video are divided into three parts. The first part illustrates the individual functions of the robot such as jumping, self-righting and steering. The second part demonstrates the robot's locomotion capability in indoor environments. Scenarios such as jumping from the floor, jumping in an office and jumping over stairs are included. The third part shows the robot's locomotion capability in outdoor environments. Experiments on uneven ground, ground with small gravels and ground with grass are included.

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.

Full body compliant humanoid COMAN

Author  IIT - Advanced Robotics

Video ID : 698

The compliant humanoid COMAN is developed by the Department of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia (IIT). http://www.iit.it/en/research/departm... All the achievements shown in this video are attributed to the team work of the Humanoid Group in ADVR, IIT.

Chapter 51 — Modeling and Control of Underwater Robots

Gianluca Antonelli, Thor I. Fossen and Dana R. Yoerger

This chapter deals with modeling and control of underwater robots. First, a brief introduction showing the constantly expanding role of marine robotics in oceanic engineering is given; this section also contains some historical backgrounds. Most of the following sections strongly overlap with the corresponding chapters presented in this handbook; hence, to avoid useless repetitions, only those aspects peculiar to the underwater environment are discussed, assuming that the reader is already familiar with concepts such as fault detection systems when discussing the corresponding underwater implementation. Themodeling section is presented by focusing on a coefficient-based approach capturing the most relevant underwater dynamic effects. Two sections dealing with the description of the sensor and the actuating systems are then given. Autonomous underwater vehicles require the implementation of mission control system as well as guidance and control algorithms. Underwater localization is also discussed. Underwater manipulation is then briefly approached. Fault detection and fault tolerance, together with the coordination control of multiple underwater vehicles, conclude the theoretical part of the chapter. Two final sections, reporting some successful applications and discussing future perspectives, conclude the chapter. The reader is referred to Chap. 25 for the design issues.

Saturation-based, nonlinear, depth-and-yaw control of an underwater vehicle

Author  Eduardo Campos-Mercado, Ahmed Chemori, Vincent Creuze, Jorge Torres-Munoz, Rogelio Lozano

Video ID : 268

This video demonstrates the robustness of a saturation-based, nonlinear controller for underwater vehicles. The performance of yaw and depth control of the L2ROV prototype is maintained, even when the buoyancy and the damping are changed. This work has been conducted by the LIRMM (University Montpellier 2, France) and the LAFMIA (CINVESTAV Mexico), in collaboration with Tecnalia France Foundation. This work has been supported by the French-Mexican PCP program and by the Region Languedoc-Roussillon.

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.

Jean Vertut master-slave manipulator arms

Author  James P. Trevelyan

Video ID : 590

Jean Vertut (http://cyberneticzoo.com/teleoperators/1970-2-virgule-remote-controlled-manipulator-jean-vertut-french/), a French engineer, is widely credited with the best and most popular designs for remotely-operated manipulators used in the nuclear industry. Research on devices for nuclear applications is described in the chapter. Here are some other reference links: http://robotics.me.utexas.edu/index.html - research group working on robots for hazardous environments. In this video, one watches the fully automatic Port-Deployed Glovebox Manipulator: Pick and Place in operation. Compare the speed and dexterity of this device with the 1950s era remotely controlled manipulator arms mentioned above. It is hard for automatic devices to even approach the speed of manually-controlled devices, even today after 60 years of robotics research and development.

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.

Diamond

Author  Tian Huang

Video ID : 47

This video demonstrates a 2-DOF high-speed parallel robot (Diamond).