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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.

Mini-Whegs™

Author  Jeremy M. Morrey, Bram Lambrecht, Andrew D. Horchler, Roy E. Ritzmann, Roger D. Quinn

Video ID : 401

The video describes a new biologically inspired robot series called Mini-Whegs™. These 8-9 cm long robots can run at sustained speeds of over 10 body lengths per second and navigate in challenging terrain.

Chapter 71 — Cognitive Human-Robot Interaction

Bilge Mutlu, Nicholas Roy and Selma Šabanović

A key research challenge in robotics is to design robotic systems with the cognitive capabilities necessary to support human–robot interaction. These systems will need to have appropriate representations of the world; the task at hand; the capabilities, expectations, and actions of their human counterparts; and how their own actions might affect the world, their task, and their human partners. Cognitive human–robot interaction is a research area that considers human(s), robot(s), and their joint actions as a cognitive system and seeks to create models, algorithms, and design guidelines to enable the design of such systems. Core research activities in this area include the development of representations and actions that allow robots to participate in joint activities with people; a deeper understanding of human expectations and cognitive responses to robot actions; and, models of joint activity for human–robot interaction. This chapter surveys these research activities by drawing on research questions and advances from a wide range of fields including computer science, cognitive science, linguistics, and robotics.

Human-robot jazz improvisation

Author  Guy Hoffman

Video ID : 236

The stage debut of Shimon, the robotic marimba player. Also, the world's first human-robot rendition of Duke Jordan's "Jordu", for human piano and robot marimba.

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.

Reconfigurable and modular robot for NOTES applications

Author  Scuola Superiore Sant'Anna, The BioRobotics Institute (Pisa, Italy)

Video ID : 833

A surgical robot is built inside the abodominal cavity, thanks to a set of modules which are introduced orally and assembled inside the body.

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.

BLUE: A biped robot with variable stiffness and damping

Author  Chengxu Zhou, Xin Wang, Zhibin Li, Nikolaos Tsagarakis

Video ID : 466

The video includes clips of the robot walking, squatting while displaying various degrees of stiffness, and the stiffness adjustment mechanism.

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 36 — Motion for Manipulation Tasks

James Kuffner and Jing Xiao

This chapter serves as an introduction to Part D by giving an overview of motion generation and control strategies in the context of robotic manipulation tasks. Automatic control ranging from the abstract, high-level task specification down to fine-grained feedback at the task interface are considered. Some of the important issues include modeling of the interfaces between the robot and the environment at the different time scales of motion and incorporating sensing and feedback. Manipulation planning is introduced as an extension to the basic motion planning problem, which can be modeled as a hybrid system of continuous configuration spaces arising from the act of grasping and moving parts in the environment. The important example of assembly motion is discussed through the analysis of contact states and compliant motion control. Finally, methods aimed at integrating global planning with state feedback control are summarized.

Whole quadruped manipulation

Author  Toru Omata et al.

Video ID : 366

The video shows a quadruped robot that can use two of its legs for whole-body manipulation of objects. The robot can stand on the knee joints of its hind legs, grasp an object with the two front legs, and adjust its center of mass by rotating the hind knee joints to manipulate it. This enables the robot to place an object on its stomach/back and use the hind legs again for walking so that the object can be moved around in the environment.

Chapter 76 — Evolutionary Robotics

Stefano Nolfi, Josh Bongard, Phil Husbands and Dario Floreano

Evolutionary Robotics is a method for automatically generating artificial brains and morphologies of autonomous robots. This approach is useful both for investigating the design space of robotic applications and for testing scientific hypotheses of biological mechanisms and processes. In this chapter we provide an overview of methods and results of Evolutionary Robotics with robots of different shapes, dimensions, and operation features. We consider both simulated and physical robots with special consideration to the transfer between the two worlds.

Evolution of cooperative and communicative behaviors

Author  Stefano Nolfi, Joachim De Greeff

Video ID : 117

A group of two e-puck robots are evolved for the capacity to reach and to move back and forth between the two circular areas. The robots are provided with infrared sensors, a camera with which they can perceive the relative position of the other robot, a microphone with which they can sense the sound-signal produced by the other robot, two motors which set the desired speed of the two wheels, and a speaker to emit sound signals. The evolved robots coordinate and cooperate on the basis of an evolved communication system which includes several implicit and explicit signals constituted, respectively, by the relative positions assumed by the robots in the environment as perceived through the robots' cameras and by the sounds with varying frequencies emitted and perceived by the robots through the robots' speakers and microphones.

Chapter 44 — Networked Robots

Dezhen Song, Ken Goldberg and Nak-Young Chong

As of 2013, almost all robots have access to computer networks that offer extensive computing, memory, and other resources that can dramatically improve performance. The underlying enabling framework is the focus of this chapter: networked robots. Networked robots trace their origin to telerobots or remotely controlled robots. Telerobots are widely used to explore undersea terrains and outer space, to defuse bombs and to clean up hazardous waste. Until 1994, telerobots were accessible only to trained and trusted experts through dedicated communication channels. This chapter will describe relevant network technology, the history of networked robots as it evolves from teleoperation to cloud robotics, properties of networked robots, how to build a networked robot, example systems. Later in the chapter, we focus on the recent progress on cloud robotics, and topics for future research.

A multi-operator, multi-robot teleoperation system

Author  Nak Young Chong

Video ID : 84

A multi-operator, multi-robot teleoperation system for collaborative maintenance operations: Video Proc. of ICRA 2001. Over the past decades, problems and notable results have been reported mainly in the single-operator single-robot (SOSR) teleoperation system. Recently, the need for cooperation has rapidly emerged in many possible applications such as plant maintenance, construction, and surgery, and considerable efforts have therefore been made toward the coordinated control of multi-operator, multi-robot (MOMR) teleoperation. We have developed coordinated control technologies for multi-telerobot cooperation in a common environment remotely controlled from multiple operators physically distant from each other. To overcome the operators' delayed visual perception arising from network throughput limitations, we have suggested several coordinated control aids at the local operator site. Operators control their master to get their telerobot to cooperate with the counterpart telerobot using the predictive simulator, as well as video image feedback. This video explains the details of the testbed and investigates the use of an online predictive simulator to assist the operator in coping with time delay.

Chapter 9 — Force Control

Luigi Villani and Joris De Schutter

A fundamental requirement for the success of a manipulation task is the capability to handle the physical contact between a robot and the environment. Pure motion control turns out to be inadequate because the unavoidable modeling errors and uncertainties may cause a rise of the contact force, ultimately leading to an unstable behavior during the interaction, especially in the presence of rigid environments. Force feedback and force control becomes mandatory to achieve a robust and versatile behavior of a robotic system in poorly structured environments as well as safe and dependable operation in the presence of humans. This chapter starts from the analysis of indirect force control strategies, conceived to keep the contact forces limited by ensuring a suitable compliant behavior to the end effector, without requiring an accurate model of the environment. Then the problem of interaction tasks modeling is analyzed, considering both the case of a rigid environment and the case of a compliant environment. For the specification of an interaction task, natural constraints set by the task geometry and artificial constraints set by the control strategy are established, with respect to suitable task frames. This formulation is the essential premise to the synthesis of hybrid force/motion control schemes.

Integration of force strategies and natural-admittance control

Author  Brian B. Mathewson, Wyatt S. Newman

Video ID : 685

When mating parts are brought together, small misalignments must be accommodated by responding to contact forces. Using force feedback, a robot may sense contact forces during assembly and invoke a response to guide the parts into their correct mating positions. The proposed approach integrates force-guided strategies into Hogan's impedance control. Stability of both geometric convergence and of contact dynamics are achieved. Geometric convergence is accomplished more reliably than through the use of impedance control alone, and such a convergence is achieved more rapidly than through the use of force-guided strategies alone. This work was published in the ICRA 1995 video proceedings.

Chapter 68 — Human Motion Reconstruction

Katsu Yamane and Wataru Takano

This chapter presents a set of techniques for reconstructing and understanding human motions measured using current motion capture technologies. We first review modeling and computation techniques for obtaining motion and force information from human motion data (Sect. 68.2). Here we show that kinematics and dynamics algorithms for articulated rigid bodies can be applied to human motion data processing, with help from models based on knowledge in anatomy and physiology. We then describe methods for analyzing human motions so that robots can segment and categorize different behaviors and use them as the basis for human motion understanding and communication (Sect. 68.3). These methods are based on statistical techniques widely used in linguistics. The two fields share the common goal of converting continuous and noisy signal to discrete symbols, and therefore it is natural to apply similar techniques. Finally, we introduce some application examples of human motion and models ranging from simulated human control to humanoid robot motion synthesis.

Example of muscle tensions computed from motion-capture data

Author  Katsu Yamane

Video ID : 763

This video shows an example of muscle tensions computed from motion-capture data. The muscle color changes from yellow to red as the tension increases. The blue lines represent tendons.