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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 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 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.

Mesoscale manipulation: System, modeling, planning and control

Author  David J. Cappelleri et al.

Video ID : 359

This video shows an example of peg-in-hole manipulation on the mesoscale. Three robust motion primitives are introduced, i.e., one-point sticking contact with counterclockwise rotation, two-point contact motion without rotation, and robust rotation. These motion primitives are sequentially executed to accomplish the peg-in-hole manipulation task.

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.

Extracting kinematic background knowledge from interactions using task-sensitive, relational learning

Author  Sebastian Hofer, Tobias Lang, Oliver Brock

Video ID : 671

To successfully manipulate novel objects, robots must first acquire information about the objects' kinematic structure. We present a method to learn relational, kinematic, background knowledge from exploratory interactions with the world. As the robot gathers experience, this background knowledge enables the acquisition of kinematic world models with increasing efficiency. Learning such background knowledge, however, proves difficult, especially in complex, feature-rich domains. We present a novel, task-sensitive, relational-rule learner and demonstrate that it is able to learn accurate kinematic background knowledge in domains where other approaches fail. The resulting background knowledge is more compact and generalizes better than that obtained with existing approaches.

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.

Playing triadic games with KASPAR

Author  Kerstin Dautenhahn

Video ID : 220

The video illustrates (using researchers taking the roles of children) the system developed by Joshua Wainer as part of his PhD research at University of Hertfordshire. In this study, KASPAR was developed to fully autonomously play games with pairs of children with autism. The robot provides encouragement, motivation and feedback, and 'joins in the game'. The system was evaluated in long-term studies with children with autism (J. Wainer et al. 2014). Results show that KASPAR encourages collaborative skills in children with autism.

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.

Teleoperation of a mini-excavator

Author  Keyvan Hashtrudi-Zaad, Simon P. DiMaio, Septimiu E. Salcudean

Video ID : 82

Teleoperation of a mini-excavator over the internet using a virtual master environment. This video is illustrates how a virtual-reality-based interface can assist users to comprehend robotic states. (See m. 44.4.3 of the Springer Handbook of Robotics, 2nd ed (2006) for details).

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.

Graph-based SLAM (Example 1)

Author  Giorgio Grisetti

Video ID : 442

This video provides an illustration of graph-based SLAM, as described in Chap. 46.3.3, Springer Handbook of Robotics, 2nd edn (2016), performed on the campus of the University of Freiburg, Germany.

Chapter 7 — Motion Planning

Lydia E. Kavraki and Steven M. LaValle

This chapter first provides a formulation of the geometric path planning problem in Sect. 7.2 and then introduces sampling-based planning in Sect. 7.3. Sampling-based planners are general techniques applicable to a wide set of problems and have been successful in dealing with hard planning instances. For specific, often simpler, planning instances, alternative approaches exist and are presented in Sect. 7.4. These approaches provide theoretical guarantees and for simple planning instances they outperform samplingbased planners. Section 7.5 considers problems that involve differential constraints, while Sect. 7.6 overviews several other extensions of the basic problem formulation and proposed solutions. Finally, Sect. 7.8 addresses some important andmore advanced topics related to motion planning.

Kinodynamic motion planning for a car-like robot

Author  Caleb Voss

Video ID : 24

In this video, the objective of the car is to reach a goal location by jumping over a ramp and pushing a block out of the way. This problem requires kinodynamic motion planning for a car-like robot using a physics simulator. This video was generated using the software tools OMPL, Blender, and MORSE.

Chapter 10 — Redundant Robots

Stefano Chiaverini, Giuseppe Oriolo and Anthony A. Maciejewski

This chapter focuses on redundancy resolution schemes, i. e., the techniques for exploiting the redundant degrees of freedom in the solution of the inverse kinematics problem. This is obviously an issue of major relevance for motion planning and control purposes.

In particular, task-oriented kinematics and the basic methods for its inversion at the velocity (first-order differential) level are first recalled, with a discussion of the main techniques for handling kinematic singularities. Next, different firstorder methods to solve kinematic redundancy are arranged in two main categories, namely those based on the optimization of suitable performance criteria and those relying on the augmentation of the task space. Redundancy resolution methods at the acceleration (second-order differential) level are then considered in order to take into account dynamics issues, e.g., torque minimization. Conditions under which a cyclic task motion results in a cyclic joint motion are also discussed; this is a major issue when a redundant manipulator is used to execute a repetitive task, e.g., in industrial applications. The use of kinematic redundancy for fault tolerance is analyzed in detail. Suggestions for further reading are given in a final section.

Configuration space control of KUKA Lightweight Robot LWR with EXARM Exoskeleton

Author  Telerobotics Lab

Video ID : 817

This video shows some advanced inverse kinematics mapping that enables the control of a redundant manipulator (KUKA LWR) by means of Cartesian location and geometric correspondence to the human arm. Thereby the null-space of the robot manipulator can be exploited to enable very intuitive operations. Joint limits and singularities are avoided, as well, by optimized mounting of the robot and the hand.

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.

REX

Author  Rex Bionics

Video ID : 511

REX, produced by REX Bionics, is an anthropomorphic lower-body robot designed to help users to stand from sitting, to ascend stair, to walk over ground, without the use of crutches.