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Chapter 66 — Robotics Competitions and Challenges

Daniele Nardi, Jonathan Roberts, Manuela Veloso and Luke Fletcher

This chapter explores the use of competitions to accelerate robotics research and promote science, technology, engineering, and mathematics (STEM) education. We argue that the field of robotics is particularly well suited to innovation through competitions. Two broad categories of robot competition are used to frame the discussion: human-inspired competitions and task-based challenges. Human-inspired robot competitions, of which the majority are sports contests, quickly move through platform development to focus on problemsolving and test through game play. Taskbased challenges attempt to attract participants by presenting a high aim for a robotic system. The contest can then be tuned, as required, to maintain motivation and ensure that the progress is made. Three case studies of robot competitions are presented, namely robot soccer, the UAV challenge, and the DARPA (Defense Advanced Research Projects Agency) grand challenges. The case studies serve to explore from the point of view of organizers and participants, the benefits and limitations of competitions, and what makes a good robot competition.

This chapter ends with some concluding remarks on the natural convergence of humaninspired competitions and task-based challenges in the promotion of STEM education, research, and vocations.

Multirobot teamwork in the CMDragons RoboCup SSL team

Author  Manuela Veloso

Video ID : 387

In this video, we can see the coordination and passing strategy as an example of the play of the RoboCup small-size league (SSL), in this case, the CMDragons team from Veloso and her students, at Carnegie Mellon University. The RoboCup SSL has an overhead camera connected to an offboard computer which plans and commands the robots: The perception, planning, and actuation cycle is fully autonomous.

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.

Structural, inspection-path planning via iterative, viewpoint resampling with application to aerial robotics

Author  Kostas Alexis

Video ID : 604

This video presents experimental results relevant for the ICRA 2015 paper: A. Bircher, K. Alexis, M. Burri, P. Oettershagen, S. Omari, T. Mantel, R. Siegwart: Structural inspection path planning via iterative viewpoint resampling with application to aerial robotics, IEEE Int. Conf. Robot. Autom. (ICRA), Seattle (2015), pp. 6423 - 6430; doi: 10.1109/ICRA.2015.7140101

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.

Robot dragonfly DelFly Explorer flies autonomously

Author  Christophe De Wagter, Sjoerd Tijmons, Bart D.W. Remes, Guido C.H.E. de Croon

Video ID : 402

The DelFly Explorer is the first flapping-wing micro air vehicle that is able to fly with complete autonomy in unknown environments. Weighing just 20 g, it is equipped with a 4 g onboard, stereo-vision system. The DelFly Explorer can perform an autonomous take-off, maintain its height, and avoid obstacles for as long as its battery lasts (~9 min). All sensing and processing is performed onboard, so no human or offboard computer is in the loop.

Chapter 50 — Modeling and Control of Robots on Rough Terrain

Keiji Nagatani, Genya Ishigami and Yoshito Okada

In this chapter, we introduce modeling and control for wheeled mobile robots and tracked vehicles. The target environment is rough terrains, which includes both deformable soil and heaps of rubble. Therefore, the topics are roughly divided into two categories, wheeled robots on deformable soil and tracked vehicles on heaps of rubble.

After providing an overview of this area in Sect. 50.1, a modeling method of wheeled robots on a deformable terrain is introduced in Sect. 50.2. It is based on terramechanics, which is the study focusing on the mechanical properties of natural rough terrain and its response to off-road vehicle, specifically the interaction between wheel/track and soil. In Sect. 50.3, the control of wheeled robots is introduced. A wheeled robot often experiences wheel slippage as well as its sideslip while traversing rough terrain. Therefore, the basic approach in this section is to compensate the slip via steering and driving maneuvers. In the case of navigation on heaps of rubble, tracked vehicles have much advantage. To improve traversability in such challenging environments, some tracked vehicles are equipped with subtracks, and one kinematical modeling method of tracked vehicle on rough terrain is introduced in Sect. 50.4. In addition, stability analysis of such vehicles is introduced in Sect. 50.5. Based on such kinematical model and stability analysis, a sensor-based control of tracked vehicle on rough terrain is introduced in Sect. 50.6. Sect. 50.7 summarizes this chapter.

A path-following control scheme for a four-wheeled mobile robot

Author  Genya Ishigami, Keiji Nagatani, Kazuya Yoshida

Video ID : 188

This video shows a feedback control for planetary rovers. It calculates both steering and driving maneuvers that can compensate for wheel slips and also enable the rover to successfully traverse a sandy slope. The performance was confirmed in slope traversal experiments using a four-wheeled rover test bed. In this split video clip, no slip control is performed on the left, and slip-compensation-feedback control is conducted on the right. The rover's motion is detected by the visual odometry system using a telecentric camera.

Chapter 61 — Robot Surveillance and Security

Wendell H. Chun and Nikolaos Papanikolopoulos

This chapter introduces the foundation for surveillance and security robots for multiple military and civilian applications. The key environmental domains are mobile robots for ground, aerial, surface water, and underwater applications. Surveillance literallymeans to watch fromabove,while surveillance robots are used to monitor the behavior, activities, and other changing information that are gathered for the general purpose of managing, directing, or protecting one’s assets or position. In a practical sense, the term surveillance is taken to mean the act of observation from a distance, and security robots are commonly used to protect and safeguard a location, some valuable assets, or personal against danger, damage, loss, and crime. Surveillance is a proactive operation,while security robots are a defensive operation. The construction of each type of robot is similar in nature with amobility component, sensor payload, communication system, and an operator control station.

After introducing the major robot components, this chapter focuses on the various applications. More specifically, Sect. 61.3 discusses the enabling technologies of mobile robot navigation, various payload sensors used for surveillance or security applications, target detection and tracking algorithms, and the operator’s robot control console for human–machine interface (HMI). Section 61.4 presents selected research activities relevant to surveillance and security, including automatic data processing of the payload sensors, automaticmonitoring of human activities, facial recognition, and collaborative automatic target recognition (ATR). Finally, Sect. 61.5 discusses future directions in robot surveillance and security, giving some conclusions and followed by references.

Tracking people for security

Author  Nikos Papanikolopoulos

Video ID : 683

Tracking of people in crowded scenes is challenging because people occlude each other as they walk around. The latest revision of the University of Minnesota's person tracker uses adaptive appearance models that explicitly account for the probability that a person may be partially occluded. All potentially occluding targets are tracked jointly, and the most likely visibility order is estimated (so we know the probability that person A is occluding person B). Target-size adaptation is performed using calibration information about the camera, and the reported target positions are made in real-world coordinates.

Chapter 21 — Actuators for Soft Robotics

Alin Albu-Schäffer and Antonio Bicchi

Although we do not know as yet how robots of the future will look like exactly, most of us are sure that they will not resemble the heavy, bulky, rigid machines dangerously moving around in old fashioned industrial automation. There is a growing consensus, in the research community as well as in expectations from the public, that robots of the next generation will be physically compliant and adaptable machines, closely interacting with humans and moving safely, smoothly and efficiently - in other terms, robots will be soft.

This chapter discusses the design, modeling and control of actuators for the new generation of soft robots, which can replace conventional actuators in applications where rigidity is not the first and foremost concern in performance. The chapter focuses on the technology, modeling, and control of lumped parameters of soft robotics, that is, systems of discrete, interconnected, and compliant elements. Distributed parameters, snakelike and continuum soft robotics, are presented in Chap. 20, while Chap. 23 discusses in detail the biomimetic motivations that are often behind soft robotics.

PETMAN tests Camo

Author  Boston Dynamics

Video ID : 457

The PETMAN robot was developed by Boston Dynamics with funding from the DoD CBD program. It is used to test the performance of protective clothing designed for hazardous environments. The video shows initial testing in a chemical protection suit and gas mask. PETMAN has sensors embedded in its skin that detect any chemicals leaking through the suit. The skin also maintains a microclimate inside the clothing by sweating and regulating temperature. Partners in developing PETMAN were MRIGlobal, Measurement Technology Northwest, Smith Carter, SRD, CUH2A, and HHI.

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.

Learning from failure I

Author  Aude Billard

Video ID : 476

This video illustrates how learning from demonstration can be bootstrapped using failed demonstrations only (in place of traditional approaches that use successful demonstrations). The algorithm is described in detail in two publications: 1)D.-H. Grollman, A. Billard: Donut as I do: Learning from failed demonstrations, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), Shanghai (2011) Best Paper Award (Cognitive Robotics); 2) D.-H. Grollman, A. Billard: Robot learning from failed demonstrations, Int. J. Social Robot. 4(4), 331-342 (2012).

Chapter 59 — Robotics in Mining

Joshua A. Marshall, Adrian Bonchis, Eduardo Nebot and Steven Scheding

This chapter presents an overview of the state of the art in mining robotics, from surface to underground applications, and beyond. Mining is the practice of extracting resources for utilitarian purposes. Today, the international business of mining is a heavily mechanized industry that exploits the use of large diesel and electric equipment. These machines must operate in harsh, dynamic, and uncertain environments such as, for example, in the high arctic, in extreme desert climates, and in deep underground tunnel networks where it can be very hot and humid. Applications of robotics in mining are broad and include robotic dozing, excavation, and haulage, robotic mapping and surveying, as well as robotic drilling and explosives handling. This chapter describes how many of these applications involve unique technical challenges for field roboticists. However, there are compelling reasons to advance the discipline of mining robotics, which include not only a desire on the part of miners to improve productivity, safety, and lower costs, but also out of a need to meet product demands by accessing orebodies situated in increasingly challenging conditions.

Autonomous loading of fragmented rock

Author  Joshua Marshall

Video ID : 718

This video shows autonomous loading of fragmented rock, first on a 1-t capacity Kubota loader at Kingston, Canada, followed by an implementation on a 14-t capacity Atlas Copco ST14 LHD in an underground mine at Kvarntorp, Sweden. The algorithm used in these demonstrations is based on force-feedback sensed in the loader cylinder pressures and utilizes an admittance control structure.

Chapter 65 — Domestic Robotics

Erwin Prassler, Mario E. Munich, Paolo Pirjanian and Kazuhiro Kosuge

When the first edition of this book was published domestic robots were spoken of as a dream that was slowly becoming reality. At that time, in 2008, we looked back on more than twenty years of research and development in domestic robotics, especially in cleaning robotics. Although everybody expected cleaning to be the killer app for domestic robotics in the first half of these twenty years nothing big really happened. About ten years before the first edition of this book appeared, all of a sudden things started moving. Several small, but also some larger enterprises announced that they would soon launch domestic cleaning robots. The robotics community was anxiously awaiting these first cleaning robots and so were consumers. The big burst, however, was yet to come. The price tag of those cleaning robots was far beyond what people were willing to pay for a vacuum cleaner. It took another four years until, in 2002, a small and inexpensive device, which was not even called a cleaning robot, brought the first breakthrough: Roomba. Sales of the Roomba quickly passed the first million robots and increased rapidly. While for the first years after Roomba’s release, the big players remained on the sidelines, possibly to revise their own designs and, in particular their business models and price tags, some other small players followed quickly and came out with their own products. We reported about theses devices and their creators in the first edition. Since then the momentum in the field of domestics robotics has steadily increased. Nowadays most big appliance manufacturers have domestic cleaning robots in their portfolio. We are not only seeing more and more domestic cleaning robots and lawn mowers on the market, but we are also seeing new types of domestic robots, window cleaners, plant watering robots, tele-presence robots, domestic surveillance robots, and robotic sports devices. Some of these new types of domestic robots are still prototypes or concept studies. Others have already crossed the threshold to becoming commercial products.

For the second edition of this chapter, we have decided to not only enumerate the devices that have emerged and survived in the past five years, but also to take a look back at how it all began, contrasting this retrospection with the burst of progress in the past five years in domestic cleaning robotics. We will not describe and discuss in detail every single cleaning robot that has seen the light of the day, but select those that are representative for the evolution of the technology as well as the market. We will also reserve some space for new types of mobile domestic robots, which will be the success stories or failures for the next edition of this chapter. Further we will look into nonmobile domestic robots, also called smart appliances, and examine their fate. Last but not least, we will look at the recent developments in the area of intelligent homes that surround and, at times, also control the mobile domestic robots and smart appliances described in the preceding sections.

Test-driving Beam, the telepresence robot

Author  Erwin Prassler

Video ID : 744

Scott Hassan from Suitable Technologies explaining the telepresence robot Beam to Parmy Olson from Forbes Magazine.

Chapter 52 — Modeling and Control of Aerial Robots

Robert Mahony, Randal W. Beard and Vijay Kumar

Aerial robotic vehicles are becoming a core field in mobile robotics. This chapter considers some of the fundamental modelling and control architectures in the most common aerial robotic platforms; small-scale rotor vehicles such as the quadrotor, hexacopter, or helicopter, and fixed wing vehicles. In order to control such vehicles one must begin with a good but sufficiently simple dynamic model. Based on such models, physically motivated control architectures can be developed. Such algorithms require realisable target trajectories along with real-time estimates of the system state obtained from on-board sensor suite. This chapter provides a first introduction across all these subjects for the quadrotor and fixed wing aerial robotic vehicles.

Autopilot using total-energy control

Author  Randy Beard

Video ID : 436

This video shows simulation results of an autopilot wich controls the lateral modes using a standard nested loop structure; the longitudinal autopilot is designed using the total-energy control structure. The commands to the autopilot are for airspeed, course angle, and altitude. The video shows a number of different step commands in these variables and the performance of a six-DOF aerodynamic model of a Zagi-style fixed-wing aircraft.