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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.

Pose graph compression for laser-based SLAM 3

Author  Cyrill Stachniss

Video ID : 451

This video illustrates pose graph compression, a technique for achieving long-term SLAM, as discussed in Chap.46.5, Springer Handbook of Robotics, 2nd edn (2016). Reference: H. Kretzschmar, C. Stachniss: Information-theoretic compression of pose graphs for laser-based SLAM, Int. J. Robot. Res. 31(11), 1219-1230 (2012).

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.

Ichthus

Author  Gi-Hun Yang, Kyung-Sik Kim, Sang-Hyo Lee, Chullhee Cho, Youngsun Ryuh

Video ID : 432

This video study captures a stage in the development of a robotic fish called ‘Ichthus’ which can be used in water-quality sensing systems. The robotic fish ‘Ichthus’ has a 3-DOF serial link-mechanism for its propulsion, which was developed at KITECH.

Chapter 6 — Model Identification

John Hollerbach, Wisama Khalil and Maxime Gautier

This chapter discusses how to determine the kinematic parameters and the inertial parameters of robot manipulators. Both instances of model identification are cast into a common framework of least-squares parameter estimation, and are shown to have common numerical issues relating to the identifiability of parameters, adequacy of the measurement sets, and numerical robustness. These discussions are generic to any parameter estimation problem, and can be applied in other contexts.

For kinematic calibration, the main aim is to identify the geometric Denavit–Hartenberg (DH) parameters, although joint-based parameters relating to the sensing and transmission elements can also be identified. Endpoint sensing or endpoint constraints can provide equivalent calibration equations. By casting all calibration methods as closed-loop calibration, the calibration index categorizes methods in terms of how many equations per pose are generated.

Inertial parameters may be estimated through the execution of a trajectory while sensing one or more components of force/torque at a joint. Load estimation of a handheld object is simplest because of full mobility and full wrist force-torque sensing. For link inertial parameter estimation, restricted mobility of links nearer the base as well as sensing only the joint torque means that not all inertial parameters can be identified. Those that can be identified are those that affect joint torque, although they may appear in complicated linear combinations.

Dynamic identification of Kuka LWR : Trajectory without load

Author  Maxime Gautier

Video ID : 482

This video shows a trajectory without load used to identify the dynamic parameters of the links, load and torque sensor gain of the Kuka LWR manipulator. Details and results are given in the papers: A. Jubien, M. Gautier, A. Janot: Dynamic identification of the Kuka LWR robot using motor torques and joint torque sensors data, preprint 19th IFAC World Congress, Cape Town (2014) pp. 8391-8396, M. Gautier, A. Jubien: Force calibration of the Kuka LWR-like robots including embedded joint torque sensors and robot structure, IEEE/RSJ Int. Conf. Intel. Robot. Syst. (IROS), Chicago (2014) pp. 416-421

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.

ACM-R5H

Author  Shigeo Hirose

Video ID : 397

The ACM-R5H is a snake robot that can go where no human can go. It is designed to perform underwater inspections and search-and-rescue missions in hazardous environments. It is a snake-like robot with extra dust sealing, waterproofing and a rigid structure that allows operation under any severe condition. It is composed of several modules with small passive wheels that allow the robot to move smoothly on surfaces. ACM-R5 can also move sinuously in underwater environments. In the front unit, a wireless camera is mounted on a special mechanism that keeps the view orientation always horizontal. ACM-R5H is ideal for inspection and search operations in underwater environments.

Controlled flight of a biologically-inspired, insect-scale robot

Author  Robert J. Wood

Video ID : 399

The Harvard Microrobotics Lab has demonstrated the first controlled flight of an insect-sized, flapping-wing robot. This video shows the 80 mg, piezoelectrically actuated robot achieving hovering flight and performing a simple lateral maneuver. Power and control signals are provided via wire tether. This work was funded by the NSF and the Wyss Institute.

Chapter 70 — Human-Robot Augmentation

Massimo Bergamasco and Hugh Herr

The development of robotic systems capable of sharing with humans the load of heavy tasks has been one of the primary objectives in robotics research. At present, in order to fulfil such an objective, a strong interest in the robotics community is collected by the so-called wearable robots, a class of robotics systems that are worn and directly controlled by the human operator. Wearable robots, together with powered orthoses that exploit robotic components and control strategies, can represent an immediate resource also for allowing humans to restore manipulation and/or walking functionalities.

The present chapter deals with wearable robotics systems capable of providing different levels of functional and/or operational augmentation to the human beings for specific functions or tasks. Prostheses, powered orthoses, and exoskeletons are described for upper limb, lower limb, and whole body structures. State-of-theart devices together with their functionalities and main components are presented for each class of wearable system. Critical design issues and open research aspects are reported.

L-Exos for upper-limb motor rehabilitation

Author  Massimo Bergamasco

Video ID : 180

The video shows the L-Exos integrated into a virtual environment, which has been specifically developed for the motor rehabilitation of the upper limb.

Chapter 8 — Motion Control

Wan Kyun Chung, Li-Chen Fu and Torsten Kröger

This chapter will focus on the motion control of robotic rigid manipulators. In other words, this chapter does not treat themotion control ofmobile robots, flexible manipulators, and manipulators with elastic joints. The main challenge in the motion control problem of rigid manipulators is the complexity of their dynamics and uncertainties. The former results from nonlinearity and coupling in the robot manipulators. The latter is twofold: structured and unstructured. Structured uncertainty means imprecise knowledge of the dynamic parameters and will be touched upon in this chapter, whereas unstructured uncertainty results from joint and link flexibility, actuator dynamics, friction, sensor noise, and unknown environment dynamics, and will be treated in other chapters. In this chapter, we begin with an introduction to motion control of robot manipulators from a fundamental viewpoint, followed by a survey and brief review of the relevant advanced materials. Specifically, the dynamic model and useful properties of robot manipulators are recalled in Sect. 8.1. The joint and operational space control approaches, two different viewpoints on control of robot manipulators, are compared in Sect. 8.2. Independent joint control and proportional– integral–derivative (PID) control, widely adopted in the field of industrial robots, are presented in Sects. 8.3 and 8.4, respectively. Tracking control, based on feedback linearization, is introduced in Sect. 8.5. The computed-torque control and its variants are described in Sect. 8.6. Adaptive control is introduced in Sect. 8.7 to solve the problem of structural uncertainty, whereas the optimality and robustness issues are covered in Sect. 8.8. To compute suitable set point signals as input values for these motion controllers, Sect. 8.9 introduces reference trajectory planning concepts. Since most controllers of robotmanipulators are implemented by using microprocessors, the issues of digital implementation are discussed in Sect. 8.10. Finally, learning control, one popular approach to intelligent control, is illustrated in Sect. 8.11.

Different jerk limits of robot-arm trajectories

Author  Torsten Kröger

Video ID : 760

This video displays the motions of a 6-DOF industrial- robot arm controlled in joint space. The first reference trajectory is not jerk-limited. The second trajectory features a joint jerk limit of 400 deg/s^3 for all six joints, and the third trajectory has a jerk limit of 20 deg/s^3 for all robot joints.

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.

Towards valve turning using a dual-arm aerial manipulator

Author  Christopher Korpela, Matko Orsag, Paul Oh, Stjepan Bogdan

Video ID : 719

A framework was proposed for valve turning using an aerial vehicle endowed with dual multi-degree of freedom manipulators. A tightly integrated control scheme between the aircraft and manipulators is mandated for tasks requiring aircraft-to-environment coupling. Feature detection is well-established for both ground and aerial vehicles and facilitates valve detection and arm tracking. Force feedback upon contact with the environment provides compliant motions in the presence of position error and coupling with the valve. The video presents results validating the valve turning framework using the proposed aircraft-arm system during flight tests.

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.

Exploitation of social cues to speed up learning

Author  Sylvain Calinon, Aude Billard

Video ID : 106

Use of social cues to speed up the imitation-learning process, with gazing and pointing information to select the objects relevant for the task. Reference: S. Calinon, A.G. Billard: Teaching a humanoid robot to recognize and reproduce social cues, Proc. IEEE Int. Symp. Robot Human Interactive Communication (Ro-Man), Hatfield (2006), pp. 346–351; URL: http://lasa.epfl.ch/research/control_automation/interaction/social/index.php .

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.

Flight stability in aerial redundant manipulators

Author  Christopher Korpela, Matko Orsag, Todd Danko, Bryan Kobe, Clayton McNeil, Robert Pisch, Paul Oh

Video ID : 693

Aerial manipulation tests conducted by the Drexel Autonomous Systems Lab.