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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.

Full body compliant humanoid COMAN

Author  IIT - Advanced Robotics

Video ID : 698

The compliant humanoid COMAN is developed by the Department of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia (IIT). http://www.iit.it/en/research/departm... All the achievements shown in this video are attributed to the team work of the Humanoid Group in ADVR, IIT.

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.

PID response to impulse in presence of link flexibility

Author  Wayne Book

Video ID : 780

A laboratory gantry robot with a final flexible link is excited by an external impulse disturbance. The video shows the very low damping of the flexible link under PID joint control. This is one of two coordinated videos, the other showing the same experiment under state feedback 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 36 — Motion for Manipulation Tasks

James Kuffner and Jing Xiao

This chapter serves as an introduction to Part D by giving an overview of motion generation and control strategies in the context of robotic manipulation tasks. Automatic control ranging from the abstract, high-level task specification down to fine-grained feedback at the task interface are considered. Some of the important issues include modeling of the interfaces between the robot and the environment at the different time scales of motion and incorporating sensing and feedback. Manipulation planning is introduced as an extension to the basic motion planning problem, which can be modeled as a hybrid system of continuous configuration spaces arising from the act of grasping and moving parts in the environment. The important example of assembly motion is discussed through the analysis of contact states and compliant motion control. Finally, methods aimed at integrating global planning with state feedback control are summarized.

Learning to place new objects

Author  Yun Jiang et al.

Video ID : 370

The video shows how to a robot learns to place objects stably in preferred locations. Four different tasks are performed: 1) loading a refrigerator, 2) loading a bookshelf, 3) cleaning a table, and 4) loading dish-racks.

Chapter 10 — Redundant Robots

Stefano Chiaverini, Giuseppe Oriolo and Anthony A. Maciejewski

This chapter focuses on redundancy resolution schemes, i. e., the techniques for exploiting the redundant degrees of freedom in the solution of the inverse kinematics problem. This is obviously an issue of major relevance for motion planning and control purposes.

In particular, task-oriented kinematics and the basic methods for its inversion at the velocity (first-order differential) level are first recalled, with a discussion of the main techniques for handling kinematic singularities. Next, different firstorder methods to solve kinematic redundancy are arranged in two main categories, namely those based on the optimization of suitable performance criteria and those relying on the augmentation of the task space. Redundancy resolution methods at the acceleration (second-order differential) level are then considered in order to take into account dynamics issues, e.g., torque minimization. Conditions under which a cyclic task motion results in a cyclic joint motion are also discussed; this is a major issue when a redundant manipulator is used to execute a repetitive task, e.g., in industrial applications. The use of kinematic redundancy for fault tolerance is analyzed in detail. Suggestions for further reading are given in a final section.

Visual servoing control of Baxter robot arms with obstacle avoidance using kinematic edundancy

Author  Chenguang Yang

Video ID : 819

Visual servoing control rby an obstacle avoidance strategy using kinematics redundancy has been developed and tested on a Baxter robot. A Point Grey Bumblebee2 stereo camera is used to obtain the 3-D point cloud of a target object. The object tracking task allocation between two arms has been developed by identifying workspaces of the dual arms and tracing the object location in a convex hull of the workspace. By employment of a simulated artificial robot as a parallel system as well as a task-switching weight factor, the robot is actually able to restore back to the natural pose smoothly in the absence of the obstacle. Two sets of experiments were carried out to demonstrate the effectiveness of the developed servoing control method.

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.

Sensor-based online trajectory generation

Author  Torsten Kröger

Video ID : 761

The video shows the movements of a position-controlled 6-DOF industrial-robot arm equipped with a distance sensor at its end-effector. The task of the robot is to draw a rectangle on the table, while the force on the table is controlled by a force controller which acts only orthogonally to the table surface. The dimensions of the rectangle are determined by the obstacles in the robot's environment. If the obstacles are moved, the distance sensor triggers the execution of a new trajectory segment which is computed within one control cycle (1 ms), so that it can be instantly executed.

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.

DLR Hand Arm System: Punching holes

Author  Alin Albu-Schäffer, Thomas Bahls, Maxime Chalon, Markus Grebenstein, Oliver Eiberger, Werner Friedl, Hannes Höppner, Dominic Lakatos, Daniel Leidner, Florian Petit, Jens Reinecke, Sebastian Wolf, Tilo Wüsthoff

Video ID : 546

The DLR Hand Arm System uses a tool to punch holes into a business card. The passive flexibility in the variable stiffness actuators (VSA) helps to keep a stable grasp during the impact and protects the hardware from damage. The movement is realized by cyclic motion control and a learning algorithm to improve the accuracy of the holes.

Chapter 76 — Evolutionary Robotics

Stefano Nolfi, Josh Bongard, Phil Husbands and Dario Floreano

Evolutionary Robotics is a method for automatically generating artificial brains and morphologies of autonomous robots. This approach is useful both for investigating the design space of robotic applications and for testing scientific hypotheses of biological mechanisms and processes. In this chapter we provide an overview of methods and results of Evolutionary Robotics with robots of different shapes, dimensions, and operation features. We consider both simulated and physical robots with special consideration to the transfer between the two worlds.

A swarm-bot of eight robots displaying coordinated motion

Author  Stefano Nolfi, Gianluca Baldassarre, Vito Trianni, Francesco Mondada, Marco Dorigo

Video ID : 115

Each robot is provided with an independent neural controller which determines the desired speed of the two wheels on the basis of the traction force caused by the movements of the other robots. The evolved robots are able to display coordinated-motion capability, independent from the way in which they are assembled, as well as to coordinate in carrying heavy objects.

Chapter 34 — Visual Servoing

François Chaumette, Seth Hutchinson and Peter Corke

This chapter introduces visual servo control, using computer vision data in the servo loop to control the motion of a robot. We first describe the basic techniques that are by now well established in the field. We give a general overview of the formulation of the visual servo control problem, and describe the two archetypal visual servo control schemes: image-based and pose-based visual servo control. We then discuss performance and stability issues that pertain to these two schemes, motivating advanced techniques. Of the many advanced techniques that have been developed, we discuss 2.5-D, hybrid, partitioned, and switched approaches. Having covered a variety of control schemes, we deal with target tracking and controlling motion directly in the joint space and extensions to under-actuated ground and aerial robots. We conclude by describing applications of visual servoing in robotics.

2.5-D VS on a 6 DOF robot arm (2)

Author  Francois Chaumette, Seth Hutchinson, Peter Corke

Video ID : 65

This video shows a 2.5-D VS on a 6 DOF robot arm with (c*^t_c, x_g, theta u_z) as visual features. It corresponds to the results depicted in Figure 34.13.

Chapter 24 — Wheeled Robots

Woojin Chung and Karl Iagnemma

The purpose of this chapter is to introduce, analyze, and compare various wheeled mobile robots (WMRs) and to present several realizations and commonly encountered designs. The mobility of WMR is discussed on the basis of the kinematic constraints resulting from the pure rolling conditions at the contact points between the wheels and the ground. Practical robot structures are classified according to the number of wheels, and features are introduced focusing on commonly adopted designs. Omnimobile robot and articulated robots realizations are described. Wheel–terrain interaction models are presented in order to compute forces at the contact interface. Four possible wheel-terrain interaction cases are shown on the basis of relative stiffness of the wheel and terrain. A suspension system is required to move on uneven surfaces. Structures, dynamics, and important features of commonly used suspensions are explained.

Articulated robot - A robot pushing 3 passive trailers

Author  Woojin Chung

Video ID : 326

An omnidirectional robot pushes three passive trailers along a straight reference trajectory. There are no actuators in the modular passive trailers, and the trailers are connected through free joints. The backward-motion controller of the robot perceives the pose of the last trailer and the joint angles between trailers. Thus, one active robot can control an arbitrary number of trailers.

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.

Using ROS4iOS

Author  François Michaud

Video ID : 419

Demonstration of the integration, using HBBA (hybrid behaviour-based architecture), of navigation, remote localization, speaker identification, speech recognition and teleoperation. The scenario employs the ROS4iOS to provide remote perceptual capabilities for visual location, speech and speaker recognition. Reference: F. Ferland, R. Chauvin, D. Létourneau, F. Michaud: Hello robot, can you come here? Using ROS4iOS to provide remote perceptual capabilities for visual location, speech and speaker recognition, Proc. Int. ACM/IEEE Conf. Human-Robot Interaction (2014), p. 101