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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.

Demonstrations and reproduction of the task of juicing an orange

Author  Florent D'Halluin, Aude Billard

Video ID : 29

Human demonstrations of the task of juicing an orange, and reproductions by the robot in new situations where the objects are located in positions not seen in the demonstrations. URL:

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.

IREP tagging spikes

Author  Nabil Simaan

Video ID : 246

This video shows telemanipulation of the IREP (insertible robotic effectors platform). The IREP is a system having 21 controllable axes including two 7-DOF dexterous arms, 3-DOF camera head, an insertion stage, and two grippers [1]. Reference: [1] A. Bajo, R. E. Goldman, L. Wang, D. Fowler, N. Simaan: Integration and preliminary evaluation of an insertable robotic effectors platform for single port access surgery, Proc. 2012 IEEE Int. Conf. Robot. Autom. (ICRA), St. Paul (2012), pp. 3381-3387

Chapter 45 — World Modeling

Wolfram Burgard, Martial Hebert and Maren Bennewitz

In this chapter we describe popular ways to represent the environment of a mobile robot. For indoor environments, which are often stored using two-dimensional representations, we discuss occupancy grids, line maps, topologicalmaps, and landmark-based representations. Each of these techniques has its own advantages and disadvantages. Whilst occupancy grid maps allow for quick access and can efficiently be updated, line maps are more compact. Also landmark-basedmaps can efficiently be updated and maintained, however, they do not readily support navigation tasks such as path planning like topological representations do.

Additionally, we discuss approaches suited for outdoor terrain modeling. In outdoor environments, the flat-surface assumption underling many mapping techniques for indoor environments is no longer valid. A very popular approach in this context are elevation and variants maps, which store the surface of the terrain over a regularly spaced grid. Alternatives to such maps are point clouds, meshes, or three-dimensional grids, which provide a greater flexibility but have higher storage demands.

3-D textured model of urban environments

Author  Michael Maurer

Video ID : 269

In this video, a micro aerial vehicle developed by the Institute for Computer Graphics and Vision, Graz Univ. of Technology, flies to predefined points and captures images for building a 3-D textured model of an urban environment. The video contains a nice description of the different steps necessary to generate a precise model by fusing the areal images with public geographic data.

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.

Three-dimensional binary manipulator

Author  Greg Chirikjian

Video ID : 161

Greg Chirikjian's binary manipulator operating in three dimensions.

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.

The long-jumping robot Grillo

Author  Umberto Scarfogliero, Cesare Stefanini, Paolo Dario

Video ID : 278

This video shows some of the very first jumping prototypes plus n animation of the simulations made on the desired gait. The robot pictured here is a quadruped, 50 mm robot that weighs about 15 g. Inspired by frog locomotion, a tiny motor loads the springs connected to the hind limbs. Equipped with a 0.2 W DC motor, the robot is configured to achieve a forward speed of 1.5 m/s.

Robotic ray takes a swim

Author  Hilary Bart-Smith

Video ID : 434

Bart-Smith's lab built the robot to mimic the nearly silent flaps of a ray's wing-like fins as it swims or glides through the water. They first began by studying living rays in the ocean and in the lab, as well as dissecting dead specimens to understand how nature engineered their bodies. Such rays can accelerate or hold position while using relatively little energy — an inspiration for making underwater drones that can stay at sea for long periods, without refueling or recharging.

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.

Biologically-inspired, multi-vehicle control algorithm

Author  Johns Hopkins University Applied Physics Laboratory

Video ID : 197

This video demonstrates a behavior-based control algorithm for autonomous operations in militarily-useful scenarios on numerous hardware platforms. This video shows that the algorithm is robust in complex operational environments, enabling the autonomous vehicle to react quickly to changing battlefield conditions.

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.

3-DOF dynamically balanced parallel robot

Author  Clément Gosselin

Video ID : 49

This video demonstrates a 3-DOF dynamically balanced parallel robot. References: 1. S. Foucault, C. Gosselin: On the development of a planar 3-DOF reactionless parallel mechanism, Proc. ASME Mech. Robot. Conf., Montréal (2002); 2. Y. Wu, C. Gosselin: Synthesis of reactionless spatial 3-DOFf and 6-DOF mechanisms without separate counter-rotations, Int. J. Robot. Res. 23(6), 625-642 (2004)

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 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.

Biped running robot MABEL

Author  Jessy Grizzle

Video ID : 533

A biped running robot MABEL developed at the University of Michigan in the lab of Prof. Grizzle. The robot was developed in collaboration with Jonathan Hurst, Al Rizzi and Jessica Hodgins of the Robotics Institute, Carnegie Mellon University.