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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.

Metamorphic robotic system

Author  Amit Pamecha, Gregory Chirikjian

Video ID : 198

This video describes a metamorphic robotic system composed of many robotic modules, each of which has the ability to locomote over its neighbors. Mechanical coupling enables the robots to interact with each other.

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.

Extended Kalman-filter SLAM

Author  John Leonard

Video ID : 455

This video shows an illustration of Kalman filter SLAM, as described in Chap. 46.3.1, Springer Handbook of Robotics, 2nd edn (2016). References: J.J. Leonard, H. Feder: A computationally efficient method for large-scale concurrent mapping and localization, Proc. Int. Symp. Robot. Res. (ISRR), Salt Lake City (2000), pp. 169–176.

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.

Snake robot in the water

Author  Shigeo Hirose

Video ID : 394

A snake-like robot swims in the water. Thanks to dust sealing and waterproofing, the robot can crawl on land with snake-like locomotion and sinuously swim in water. The robot is composed of compact modules with small passive wheels along the outer edges of their fins.

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 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.

Reaching in clutter with whole-arm tactile sensing

Author  Advait Jain, Marc D. Killpack, Aaron Edsinger, Charles C. Kemp

Video ID : 674

In this video, our robot Cody attempts to reach to five different goal locations using four attempts (meaning four different base locations) for each goal. For each goal, we test our single-step, quasi-static, model-predictive controller against the performance of a baseline kinematic controller that has compliance at the joints.

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 FLEA: Flea-inspired, light jumping robot using elastic catapult with active storage and release mechanism

Author  Minkyun Noh, Seung-Won Kim, Sungmin An, Je-Sung Koh, Kyu-Jin Cho

Video ID : 281

The FLEA: flea-inspired, light jumping robot using elastic catapult with active storage and release mechanism. The robot was created to realize a flea-inspired catapult mechanism with shape-memory-alloy (SMA) spring actuators and a smart composite microstructure. The robot was fabricated with a weight of 1.1 g and a 2 cm body size, so that it can jump a distance of up to 30 times its body size.

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.

Promotional video of robot for cleaning up Fukushima

Author  James P. Trevelyan

Video ID : 583

Many companies have proposed new robots to help with the Fukushima reactor decommissioning process. This is one of many such promotional videos.

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.

Catching objects in flight

Author  Seungsu Kim, Ashwini Shukla, Aude Billard

Video ID : 653

We target the difficult problem of catching in-flight objects with uneven shapes. This requires the solution of three complex problems: predicting accurately the trajectory of fast-moving objects, predicting the feasible catching configuration, and planning the arm motion, all within milliseconds. We follow a programming-by-demonstration approach in order to learn models of the object and the arm dynamics from throwing examples. We propose a new methodology for finding a feasible catching configuration in a probabilistic manner. We leverage the strength of dynamical systems for encoding motion from several demonstrations. This enables fast and online adaptation of the arm motion in the presence of sensor uncertainty. We validate the approach in simulation with the iCub humanoid robot and in real-world experiment with the KUKA LWR 4+ (7-DOF arm robot) for catching a hammer, a tennis racket, an empty bottle, a partially filled bottle and a cardboard box.

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.

Indoor, urban aerial vehicle navigation

Author  Jonathan How

Video ID : 703

The MIT indoor multi-vehicle testbed is specially designed to study long duration missions in a controlled, urban environment. This testbed is being used to implement and analyze the performance of techniques for embedding the fleet and vehicle health state into the mission and UAV planning. More than four air vehicles can be flown in a typical-sized room, and it takes no more than one operator to set up the platform for flight testing at any time of day and for any length of time. At the heart of the testbed is a global metrology system that yields very accurate, high bandwidth position and attitude data for all vehicles in the entire room.

Chapter 62 — Intelligent Vehicles

Alberto Broggi, Alex Zelinsky, Ümit Özgüner and Christian Laugier

This chapter describes the emerging robotics application field of intelligent vehicles – motor vehicles that have autonomous functions and capabilities. The chapter is organized as follows. Section 62.1 provides a motivation for why the development of intelligent vehicles is important, a brief history of the field, and the potential benefits of the technology. Section 62.2 describes the technologies that enable intelligent vehicles to sense vehicle, environment, and driver state, work with digital maps and satellite navigation, and communicate with intelligent transportation infrastructure. Section 62.3 describes the challenges and solutions associated with road scene understanding – a key capability for all intelligent vehicles. Section 62.4 describes advanced driver assistance systems, which use the robotics and sensing technologies described earlier to create new safety and convenience systems for motor vehicles, such as collision avoidance, lane keeping, and parking assistance. Section 62.5 describes driver monitoring technologies that are being developed to mitigate driver fatigue, inattention, and impairment. Section 62.6 describes fully autonomous intelligent vehicles systems that have been developed and deployed. The chapter is concluded in Sect. 62.7 with a discussion of future prospects, while Sect. 62.8 provides references to further reading and additional resources.

Inria/Ligier automated parallel-parking demo in an open parking area

Author  Christian Laugier, Igor Paromtchik

Video ID : 567

This video shows a pioneer demonstration of the concept of "autonomous parallel parking" on the early Inria/Ligier autonomous vehicle (1996). The approach does not require any prior model of the parking area. The car is controlled using information coming from inexpensive, on-board sensors, and motion control decisions (including parking maneuvers) are taken online according to the state of the sensed environment. Public demonstrations of the systems have been performed during several publicized and scientific events (including during three days at the IEEE/RSJ IROS 1997 Conference). More technical details can be found in [62.89].