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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.

The Crystal Ball: Predicting future motions

Author  Katsu Yamane

Video ID : 764

This video shows a demonstration of The Crystal Ball, a system that predicts future motions based on a graphical motion model. The rightmost figure represents the current motion, while the other figures represent the predicted motions.

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.

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.

OctoMap visualization

Author  Maren Bennewitz, Wolfram Burgard, Armin Hornung, Cyrill Stachniss, Kai Wurm

Video ID : 79

This video shows the Freiburg Computer Science campus in a 3-D OctoMap. Note that free space is also encoded, although not shown in the video. The map covers an area of 292 x 167 x 28 m^3 and requires only 130 MB in memory at 20 cm resolution.

Chapter 26 — Flying Robots

Stefan Leutenegger, Christoph Hürzeler, Amanda K. Stowers, Kostas Alexis, Markus W. Achtelik, David Lentink, Paul Y. Oh and Roland Siegwart

Unmanned aircraft systems (UASs) have drawn increasing attention recently, owing to advancements in related research, technology, and applications. While having been deployed successfully in military scenarios for decades, civil use cases have lately been tackled by the robotics research community.

This chapter overviews the core elements of this highly interdisciplinary field; the reader is guided through the design process of aerial robots for various applications starting with a qualitative characterization of different types of UAS. Design and modeling are closely related, forming a typically iterative process of drafting and analyzing the related properties. Therefore, we overview aerodynamics and dynamics, as well as their application to fixed-wing, rotary-wing, and flapping-wing UAS, including related analytical tools and practical guidelines. Respecting use-case-specific requirements and core autonomous robot demands, we finally provide guidelines to related system integration challenges.

UAV stabilization, mapping and obstacle avoidance using VI-Sensor

Author  Skybotix AG

Video ID : 689

The video depicts UAV stabilization, mapping and obstacle avoidance using the Skybotix--Autonomous Systems Lab VI-Sensor - on-board and realtime. The robot is enabled with assisted teleoperation without line of sight and without the use of GPS during the ICARUS trials in Marche-En-Famenne.

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.

Incremental learning of finger manipulation with tactile capability

Author  Eric Sauser, Brenna Argall, Aude Billard

Video ID : 104

Incremental learning of fingers manipulation skill, first demonstrated through a dataglove and then refined through kinesthetic teaching by exploiting the tactile capabilities of the iCub humanoid robot. Reference: E.L. Sauser, B.D. Argall, G. Metta, A.G. Billard: Iterative learning of grasp adaptation through human corrections, Robot. Auton. Syst. 60(1), 55–71 (2012); URL: .

Chapter 13 — Behavior-Based Systems

François Michaud and Monica Nicolescu

Nature is filled with examples of autonomous creatures capable of dealing with the diversity, unpredictability, and rapidly changing conditions of the real world. Such creatures must make decisions and take actions based on incomplete perception, time constraints, limited knowledge about the world, cognition, reasoning and physical capabilities, in uncontrolled conditions and with very limited cues about the intent of others. Consequently, one way of evaluating intelligence is based on the creature’s ability to make the most of what it has available to handle the complexities of the real world. The main objective of this chapter is to explain behavior-based systems and their use in autonomous control problems and applications. The chapter is organized as follows. Section 13.1 overviews robot control, introducing behavior-based systems in relation to other established approaches to robot control. Section 13.2 follows by outlining the basic principles of behavior-based systems that make them distinct from other types of robot control architectures. The concept of basis behaviors, the means of modularizing behavior-based systems, is presented in Sect. 13.3. Section 13.4 describes how behaviors are used as building blocks for creating representations for use by behavior-based systems, enabling the robot to reason about the world and about itself in that world. Section 13.5 presents several different classes of learning methods for behavior-based systems, validated on single-robot and multirobot systems. Section 13.6 provides an overview of various robotics problems and application domains that have successfully been addressed or are currently being studied with behavior-based control. Finally, Sect. 13.7 concludes the chapter.

Experience-based learning of high-level task representations: Demonstration

Author  Monica Nicolescu

Video ID : 27

This is a video recorded in early 2000s, showing a Pioneer robot learning to visit a number of targets in a certain order - the human demonstration stage. The robot execution stage is also shown in a related video in this chapter. References: 1. M. Nicolescu, M.J. Mataric: Experience-based learning of task representations from human-robot interaction, Proc. IEEE Int. Symp. Comput. Intell. Robot. Autom. Banff (2001), pp. 463-468; 2. M. Nicolescu, M.J. Mataric: Learning and interacting in human-robot domains, IEEE Trans. Syst. Man Cybernet. A31(5), 419-430 (2001)

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.

1961 nuclear-reactor meltdown : The SL-1 accident - United States Army Documentary - WDTVLIVE42

Author  James P. Trevelyan

Video ID : 589

This archive film, though long, provides graphic details on a relatively modest nuclear accident illustrating the difficulties that still face researchers working to provide robotic solutions.

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 ROKVISS camera images pulling spring

Author  Gerd Hirzinger, Klaus Landzettel

Video ID : 334

ROKVISS manipulating the handles of springs to verify the long-term performance of the torque-controlled joints. The stereo-camera view from an actual robot end-effector is shown. At first, the robot performs an inspection maneuver. Then, it pulls on the spring in the experimental task board, with two different oscillation frequencies, to gain measurement data on the robot-joint's parameters (stiffness, temperature-dependent friction, etc.).

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.

Bimanual dissection

Author  Pierre Dupont

Video ID : 249

This 2011 video demonstrates bimanual, teleoperated tissue dissection using a CO2 laser and 1 mm-wide forceps at the Pediatric Cardiac Bioengeneering Lab at Boston Children's Hospital.

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 heterogeneous multiple-operator, multiple-robot system.

Author  Paulo Sousa Dias, Jose Pinto, Rui Goncalves

Video ID : 81

A heterogeneous multiple-operator, multiple-robot system. The video explains how different kinds of multiple underwater vehicles can be teleoperated by multiple human operators to perform multiple tasks simultaneously, a great example of multiple-operator, multiple-robot systems.