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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.

RHex rough-terrain robot

Author  Boston Dynamics

Video ID : 536

A leg-wheel hybrid robot RHex developed by Boston Dynamics.

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.

Tele-actor

Author  Ken Goldberg, Dezhen Song

Video ID : 83

We describe a networked teleoperation system that enables groups of participants to collaboratively explore real-time remote environments. Participants collaborate using a spatial dynamic voting (SDV) interface which enables them to vote on a sequence of images via a network such as the internet. The SDV interface runs on each client computer and communicates with a central server which collects, displays, and analyzes time sequences of spatial votes. The results are conveyed to the “tele-actor,” a skilled human with cameras and microphones who navigates and performs actions in the remote environment.

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.

Policy learning

Author  Peter Pastor

Video ID : 668

The video explains and demonstrates the basics of policy learning as based on two tasks, pool strokes and chopstick manipulation.

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.

Dive with REMUS

Author  Woods Hole Oceanographic Institution

Video ID : 87

Travel with a REMUS 100 autonomous, underwater vehicle on a dive off the Carolina coast to study the connection between the physical processes in the ocean at the edge of the continental shelf and the things that live there. Video footage by Chris Linder. Funding by the Department of the Navy, Science & Technology; and Centers for Ocean Sciences Education Excellence (COSEE).

Chapter 79 — Robotics for Education

David P. Miller and Illah Nourbakhsh

Educational robotics programs have become popular in most developed countries and are becoming more and more prevalent in the developing world as well. Robotics is used to teach problem solving, programming, design, physics, math and even music and art to students at all levels of their education. This chapter provides an overview of some of the major robotics programs along with the robot platforms and the programming environments commonly used. Like robot systems used in research, there is a constant development and upgrade of hardware and software – so this chapter provides a snapshot of the technologies being used at this time. The chapter concludes with a review of the assessment strategies that can be used to determine if a particular robotics program is benefitting students in the intended ways.

Hampton Robotics Club

Author  cscsteam

Video ID : 239

A documentary which follows the very successful Hampton Robotics Club and their devotion to the popular activity Botball. Submitted to the 2014 i5 Film Competition by Hampton High School.

Chapter 74 — Learning from Humans

Aude G. Billard, Sylvain Calinon and Rüdiger Dillmann

This chapter surveys the main approaches developed to date to endow robots with the ability to learn from human guidance. The field is best known as robot programming by demonstration, robot learning from/by demonstration, apprenticeship learning and imitation learning. We start with a brief historical overview of the field. We then summarize the various approaches taken to solve four main questions: when, what, who and when to imitate. We emphasize the importance of choosing well the interface and the channels used to convey the demonstrations, with an eye on interfaces providing force control and force feedback. We then review algorithmic approaches to model skills individually and as a compound and algorithms that combine learning from human guidance with reinforcement learning. We close with a look on the use of language to guide teaching and a list of open issues.

Probabilistic encoding of motion in a subspace of reduced dimensionality

Author  Keith Grochow, Steven Martin, Aaron Hertzmann, Zoran Popovic

Video ID : 102

Probabilistic encoding of motion in a subspace of reduced dimensionality. Reference: K. Grochow, S. L. Martin, A. Hertzmann, Z. Popovic: Style-based inverse kinematics, Proc. ACM Int. Conf. Comput. Graphics Interact. Tech. (SIGGRAPH), 522–531 (2004); URL: http://grail.cs.washington.edu/projects/styleik/ .

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.

Modsnake pole climb

Author  Howie Choset

Video ID : 171

CMU Modsnake climbing and navigating curves on a jagged pole.

Chapter 6 — Model Identification

John Hollerbach, Wisama Khalil and Maxime Gautier

This chapter discusses how to determine the kinematic parameters and the inertial parameters of robot manipulators. Both instances of model identification are cast into a common framework of least-squares parameter estimation, and are shown to have common numerical issues relating to the identifiability of parameters, adequacy of the measurement sets, and numerical robustness. These discussions are generic to any parameter estimation problem, and can be applied in other contexts.

For kinematic calibration, the main aim is to identify the geometric Denavit–Hartenberg (DH) parameters, although joint-based parameters relating to the sensing and transmission elements can also be identified. Endpoint sensing or endpoint constraints can provide equivalent calibration equations. By casting all calibration methods as closed-loop calibration, the calibration index categorizes methods in terms of how many equations per pose are generated.

Inertial parameters may be estimated through the execution of a trajectory while sensing one or more components of force/torque at a joint. Load estimation of a handheld object is simplest because of full mobility and full wrist force-torque sensing. For link inertial parameter estimation, restricted mobility of links nearer the base as well as sensing only the joint torque means that not all inertial parameters can be identified. Those that can be identified are those that affect joint torque, although they may appear in complicated linear combinations.

Dynamic identification of Staubli TX40 : Trajectory without load

Author  Maxime Gautier

Video ID : 480

This video shows a trajectory without load used to identify the dynamic parameters of the links, the load and the joint drive chain of an industrial Staubli TX 40 manipulator. Details and results are provided in the paper: M. Gautier, S. Briot: Global identification of joint drive gains and dynamic parameters of robots, ASME J. Dyn. Syst. Meas. Control 136(5), 051025-051025-9 (2014); doi:10.1115/1.4027506