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Chapter 39 — Cooperative Manipulation

Fabrizio Caccavale and Masaru Uchiyama

This chapter is devoted to cooperative manipulation of a common object by means of two or more robotic arms. The chapter opens with a historical overview of the research on cooperativemanipulation, ranging from early 1970s to very recent years. Kinematics and dynamics of robotic arms cooperatively manipulating a tightly grasped rigid object are presented in depth. As for the kinematics and statics, the chosen approach is based on the socalled symmetric formulation; fundamentals of dynamics and reduced-order models for closed kinematic chains are discussed as well. A few special topics, such as the definition of geometrically meaningful cooperative task space variables, the problem of load distribution, and the definition of manipulability ellipsoids, are included to give the reader a complete picture ofmodeling and evaluation methodologies for cooperative manipulators. Then, the chapter presents the main strategies for controlling both the motion of the cooperative system and the interaction forces between the manipulators and the grasped object; in detail, fundamentals of hybrid force/position control, proportional–derivative (PD)-type force/position control schemes, feedback linearization techniques, and impedance control approaches are given. In the last section further reading on advanced topics related to control of cooperative robots is suggested; in detail, advanced nonlinear control strategies are briefly discussed (i. e., intelligent control approaches, synchronization control, decentralized control); also, fundamental results on modeling and control of cooperative systems possessing some degree of flexibility are briefly outlined.

Cooperative grasping and transportation of an object using two industrial manipulators

Author  Francesco Basile, Fabrizio Caccavale, Pasquale Chiacchio, Jolanda Coppola, Alessandro Marino

Video ID : 69

This video shows an example of cooperative grasping and transportation of an object using two industrial manipulators. A two-layer hierarchical, kinematic control is adopted, based on a suitable task formulation for general multi-arm systems. Reference: F. Basile, F. Caccavale, P. Chiacchio, J. Coppola, A. Marino: A decentralized kinematic control architecture for collaborative and cooperative multi-arm systems, Mechatronics, 23, 1100-1112 (2013).

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.

Chapter 11 — Robots with Flexible Elements

Alessandro De Luca and Wayne J. Book

Design issues, dynamic modeling, trajectory planning, and feedback control problems are presented for robot manipulators having components with mechanical flexibility, either concentrated at the joints or distributed along the links. The chapter is divided accordingly into two main parts. Similarities or differences between the two types of flexibility are pointed out wherever appropriate.

For robots with flexible joints, the dynamic model is derived in detail by following a Lagrangian approach and possible simplified versions are discussed. The problem of computing the nominal torques that produce a desired robot motion is then solved. Regulation and trajectory tracking tasks are addressed by means of linear and nonlinear feedback control designs.

For robots with flexible links, relevant factors that lead to the consideration of distributed flexibility are analyzed. Dynamic models are presented, based on the treatment of flexibility through lumped elements, transfer matrices, or assumed modes. Several specific issues are then highlighted, including the selection of sensors, the model order used for control design, and the generation of effective commands that reduce or eliminate residual vibrations in rest-to-rest maneuvers. Feedback control alternatives are finally discussed.

In each of the two parts of this chapter, a section is devoted to the illustration of the original references and to further readings on the subject.

State feedback response to impulse in presence of link flexibility

Author  Wayne Book

Video ID : 781

A laboratory gantry robot with a final flexible link is excited by an external impulse disturbance. The video shows the effective damping obtained using full state feedback control with an accurately tuned estimator. The reduction in settling time compared to PID joint control is dramatic. This is one of two coordinated videos, the other showing the same experiment under PID control. Reference: B. Post: Robust State Estimation for the Control of Flexible Robotic Manipulators, Dissertation, School of Mechanical Engineering, Georgia Institute of Technology, Atlanta (2013)

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.

RHex the parkour robot

Author  Uluc Saranli, Martin Buehler, Daniel E. Koditschek

Video ID : 400

RHex is an all-terrain walking robot that could conceivably one day climb over rubble in a rescue mission or cross the desert with environmental sensors strapped to its back. The name is pronounced "Rex" like the over-excited puppy it resembles when it is bounding over the ground; RHex is short for "robot hexapod", a name that stems from its six springy legs.

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.

Development of the humanoid robot DARwIn

Author  Dennis Hong

Video ID : 526

The design and development process for humanoid robots by Dr. Muecke and Prof. Hong.

Chapter 30 — Sonar Sensing

Lindsay Kleeman and Roman Kuc

Sonar or ultrasonic sensing uses the propagation of acoustic energy at higher frequencies than normal hearing to extract information from the environment. This chapter presents the fundamentals and physics of sonar sensing for object localization, landmark measurement and classification in robotics applications. The source of sonar artifacts is explained and how they can be dealt with. Different ultrasonic transducer technologies are outlined with their main characteristics highlighted.

Sonar systems are described that range in sophistication from low-cost threshold-based ranging modules to multitransducer multipulse configurations with associated signal processing requirements capable of accurate range and bearing measurement, interference rejection, motion compensation, and target classification. Continuous-transmission frequency-modulated (CTFM) systems are introduced and their ability to improve target sensitivity in the presence of noise is discussed. Various sonar ring designs that provide rapid surrounding environmental coverage are described in conjunction with mapping results. Finally the chapter ends with a discussion of biomimetic sonar, which draws inspiration from animals such as bats and dolphins.

Monash DSP sonar tracking a moving plane

Author  Lindsay Kleeman

Video ID : 313

A four-transducer system is controlled with a DSP microcontroller which processes echoes to determine the normal incidence and range to a plane reflector. The transducer scans to locate the plane and then tracks the normal-incidence section of the plane as it moves in real time.

Chapter 7 — Motion Planning

Lydia E. Kavraki and Steven M. LaValle

This chapter first provides a formulation of the geometric path planning problem in Sect. 7.2 and then introduces sampling-based planning in Sect. 7.3. Sampling-based planners are general techniques applicable to a wide set of problems and have been successful in dealing with hard planning instances. For specific, often simpler, planning instances, alternative approaches exist and are presented in Sect. 7.4. These approaches provide theoretical guarantees and for simple planning instances they outperform samplingbased planners. Section 7.5 considers problems that involve differential constraints, while Sect. 7.6 overviews several other extensions of the basic problem formulation and proposed solutions. Finally, Sect. 7.8 addresses some important andmore advanced topics related to motion planning.

Motion planning in multi-robot scenario.

Author  Jamie Snape, Jur van den Berg, Stephen J. Guy, Dinesh Manocha

Video ID : 22

Motion planning can be used for multiple robot scenarios. In this video, each iRobot Roomba senses its surroundings and acts independently without central coordination or communication with other robots. This approach uses the current position and the velocity of other robots to predict their future trajectories in order to avoid collisions.

Chapter 71 — Cognitive Human-Robot Interaction

Bilge Mutlu, Nicholas Roy and Selma Šabanović

A key research challenge in robotics is to design robotic systems with the cognitive capabilities necessary to support human–robot interaction. These systems will need to have appropriate representations of the world; the task at hand; the capabilities, expectations, and actions of their human counterparts; and how their own actions might affect the world, their task, and their human partners. Cognitive human–robot interaction is a research area that considers human(s), robot(s), and their joint actions as a cognitive system and seeks to create models, algorithms, and design guidelines to enable the design of such systems. Core research activities in this area include the development of representations and actions that allow robots to participate in joint activities with people; a deeper understanding of human expectations and cognitive responses to robot actions; and, models of joint activity for human–robot interaction. This chapter surveys these research activities by drawing on research questions and advances from a wide range of fields including computer science, cognitive science, linguistics, and robotics.

Robotic secrets revealed, Episode 2: The trouble begins

Author  Greg Trafton

Video ID : 130

This video demonstrates research on robot perception (including object recognition and multimodal person identification) and embodied cognition (including theory of mind or the ability to reason about what others believe). The video features two people interacting with two robots.

Chapter 41 — Active Manipulation for Perception

Anna Petrovskaya and Kaijen Hsiao

This chapter covers perceptual methods in which manipulation is an integral part of perception. These methods face special challenges due to data sparsity and high costs of sensing actions. However, they can also succeed where other perceptual methods fail, for example, in poor-visibility conditions or for learning the physical properties of a scene.

The chapter focuses on specialized methods that have been developed for object localization, inference, planning, recognition, and modeling in activemanipulation approaches.We concludewith a discussion of real-life applications and directions for future research.

Tactile localization of a power drill

Author  Kaijen Hsiao

Video ID : 77

This video shows a Barrett WAM arm tactilely localizing and reorienting a power drill under high positional uncertainty. The goal is for the robot to robustly grasp the power drill such that the trigger can be activated. The robot tracks the distribution of possible object poses on the table over a 3-D grid (the belief space). It then selects between information-gathering, reorienting, and goal-seeking actions by modeling the problem as a POMDP (partially observable Markov decision process) and using receding-horizon, forward search through the belief space. In the video, the inset window with the simulated robot is a visualization of the current belief state. The red spheres sit at the vertices of the object mesh placed at the most likely state, and the dark-blue box also shows the location of the most likely state. The purple box shows the location of the mean of the belief state, and the light-blue boxes show the variance of the belief state in the form of the locations of various states that are one standard deviation away from the mean in each of the three dimensions of uncertainty (x, y, and theta). The magenta spheres and arrows that appear when the robot touches the object show the contact locations and normals as reported by the sensors, and the cyan spheres that largely overlap the hand show where the robot controllers are trying to move the hand.

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.

Security: Facial recognition

Author  Ali Mollahosseini, Mohammad Mahoor

Video ID : 553

Video of face tracking and facial-landmark-point extraction of Ali's face for a security robot.