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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.

An octopus-bioinspired solution to movement and manipulation for soft robots

Author  Marcello Calisti, Michelle Giorelli, Guy Levy, Barbara Mazzolai, Binyamin Hochner, Cecilia Laschi, Paolo Dario

Video ID : 411

A totally soft robotic arm freely moving in water was inspired by the form and morphology of the octopus.

Chapter 53 — Multiple Mobile Robot Systems

Lynne E. Parker, Daniela Rus and Gaurav S. Sukhatme

Within the context of multiple mobile, and networked robot systems, this chapter explores the current state of the art. After a brief introduction, we first examine architectures for multirobot cooperation, exploring the alternative approaches that have been developed. Next, we explore communications issues and their impact on multirobot teams in Sect. 53.3, followed by a discussion of networked mobile robots in Sect. 53.4. Following this we discuss swarm robot systems in Sect. 53.5 and modular robot systems in Sect. 53.6. While swarm and modular systems typically assume large numbers of homogeneous robots, other types of multirobot systems include heterogeneous robots. We therefore next discuss heterogeneity in cooperative robot teams in Sect. 53.7. Once robot teams allow for individual heterogeneity, issues of task allocation become important; Sect. 53.8 therefore discusses common approaches to task allocation. Section 53.9 discusses the challenges of multirobot learning, and some representative approaches. We outline some of the typical application domains which serve as test beds for multirobot systems research in Sect. 53.10. Finally, we conclude in Sect. 53.11 with some summary remarks and suggestions for further reading.

Swarm construction robots

Author  Radhika Nagpal

Video ID : 216

This video describes produced at Harvard's Wyss Institute for Biologically Inspired Engineering, showing the development of swarm robots for construction. These robots follow the biological principles underlying insect swarms to achieve their constructions. The robots follow local control roles that, together with traffic control laws, guarantee the building of desired structures.

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 DEOS demonstration mission simulation

Author  Roberto Lampariello, Gerd Hirzinger

Video ID : 339

This video simulation shows an intended task in DLR's DEOS project for grasping an uncooperative, tumbling target satellite (left) by means of a free-flying robot (right, servicer satellite and robot manipulator). The task consists of approaching a predefined point on the target with the robot end-effector, tracking the same point with the robot end-effector while homing in onto it, closing the grasp, and stabilizing the relative motion between the two spacecraft. Following this, the robot performs a berthing task to secure the target in a dedicated docking port on the servicer. The servicer's GNC system is switched off during the entire duration of the grasping maneuver, giving rise to free-floating dynamic behavior of the manipulator. The complete robot trajectory is provided by a motion planner in order to guarantee feasibility with respect to motion constraints, such as the the field of view of the end-effector camera, etc.

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.

Global Conference on Educational Robotics and International Botball Tournament

Author  KIPR

Video ID : 241

GCER is a STEM-oriented robotics conference, in which the majority of the attendees, paper authors, and presenters are K-12 robotics students. Educator-paper tracks and technology-research tracks also occur. GCER is also the site of the International Botball Tournament, KIPR Open, aerial robots contests, and elementary-school robotics challenges. Some of the recent guest speakers at the conference have included Dr. Maja Mataric (human-robot interactions), Dr. Vijay Kumar (coordinated flying robots), and Dr. Hiroshi Ishiguro (androids). Details from: http://www.kipr.org/gcer .

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.

Discrimination of objects through sensory-motor coordination

Author  Stefano Nolfi

Video ID : 116

A Khepera robot provided with infrared sensors is evolved for the ability to find and remain close to a cylindrical object randomly located in the environment. The discrimination of the two types of objects (walls and cylinders) is realized by exploiting the limit-cycle oscillatory behavio,r which is produced by the robot near the cylinder and which emerges from the robot/environmental interactions (i.e., by the interplay between the way in which the robot react to sensory stimuli and the perceptual consequences of the robot actions).

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.

CLASH: Climbing loose vertical cloth

Author  Paul Birkmeyer, Andrew G. Gillies, Ronald S. Fearing

Video ID : 391

CLASH is a 10 cm, 15 g robot capable of climbing vertical loose-cloth surfaces at 15 cm/s. The robot has a single actuator driving its six legs which are equipped with novel passive foot mechanisms to facilitate smooth engagement and disengagement of spines. Descended from the DASH hexapedal robot, CLASH features a redesigned transmission with a lower profile and improved dynamics for climbing.

Chapter 15 — Robot Learning

Jan Peters, Daniel D. Lee, Jens Kober, Duy Nguyen-Tuong, J. Andrew Bagnell and Stefan Schaal

Machine learning offers to robotics a framework and set of tools for the design of sophisticated and hard-to-engineer behaviors; conversely, the challenges of robotic problems provide both inspiration, impact, and validation for developments in robot learning. The relationship between disciplines has sufficient promise to be likened to that between physics and mathematics. In this chapter, we attempt to strengthen the links between the two research communities by providing a survey of work in robot learning for learning control and behavior generation in robots. We highlight both key challenges in robot learning as well as notable successes. We discuss how contributions tamed the complexity of the domain and study the role of algorithms, representations, and prior knowledge in achieving these successes. As a result, a particular focus of our chapter lies on model learning for control and robot reinforcement learning. We demonstrate how machine learning approaches may be profitably applied, and we note throughout open questions and the tremendous potential for future research.

Inverted helicopter hovering

Author  Pieter Abbeel

Video ID : 352

An example of simulation-based optimization using a learned forward model. This brief video shows a successful application of reinforcement learning to the design of a controller for sustained inverted flight of an autonomous helicopter. The authors began by learning a stochastic, nonlinear forward model of the helicopter’s dynamics. Then, a reinforcement learning algorithm was applied to automatically learn a controller for autonomous inverted hovering. The video illustrates Section 15.2.5 -- Applications of Model Learning, Springer Handbook of Robotics, 2nd ed (2016); Reference: A.Y. Ng, A. Coates, M. Diel, V. Ganapathi, J. Schulte, B. Tse, E. Berger, E. Liang: Autonomous inverted helicopter flight via reinforcement learning, IX Int. Symp. Exp. Robot. 2004, Springer Tract. Adv. Robot. 21, 363-372 (2006)

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.