Sensors and Actuators For Mechatronics System

 Sensors and Actuators For Mechatronics System

Sensors and actuators play an important role in robotic manipulation and its applications. They must operate precisely and function reliably as they directly influence the performance of the robot operation. A transducer, a sensor or actuator, like most devices, is described by a number of characteristics and distinctive features. In this section, we describe in detail the different sensing and actuation methods for robotic applications, the operating principle describing the energy conversion, and various significant designs that incorporate these methods. This section is divided into four subsections, namely, tactile and proximity sensors, force sensors, vision, and actuators.

 By definition, tactile sensing is the continuously variable sensing of forces and force gradients over an area. This task is usually performed by an m × n array of industrial sensors called forcels. By considering the outputs from all of the individual forcels, it is possible to construct a tactile image of the targeted object. This ability is a form of sensory feedback which is important in development of robots. These robots will incorporate tactile sensing pads in their end effectors. By using the tactile image of the grasped object, it will be possible to determine such factors as the presence, size, shape, texture, and thermal conductivity of the grasped object. The location and orientation of the object as well as reaction forces and moments could also be detected. Finally, the tactile image could be used to detect the onset of part slipping. Much of the tactile sensor data processing is parallel with that of the vision sensing. Recognition of contacting objects by extracting and classifying features in the tactile image has been a primary goal. Thus, the description of tactile sensor in the following subsection will be focused on transduction methods and their relative advantages and disadvantages.

Proximity sensing, on the other hand, is the detection of approach to a workplace or obstacle prior to touching. Proximity sensing is required for really competent general-purpose robots. Even in a highly structured environment where object location is presumably known, accidental collision may occur, and foreign object could intrude. Avoidance of damaging collision is imperative. However, even if the environment is structured as planned, it is often necessary to slow a working manipulator from a high slew rate to a slow approach just prior to touch. Since workpiece position accuracy always has some tolerance, proximity sensing is still useful.

Many robotic processes require sensors to transduce contact force information for use in loop closure and data gathering functions. Contact sensors, wrist force/torque sensors, and force probes are used in many applications such as grasping, assembly, and part inspection. Unlike tactile sensing which measures pressure over a relatively large area, force sensing measures action applied to a spot. Tactile sensing concerns extracting features of the object being touched, whereas quantitative measurement is of par- ticular interest in force sensing. However, many transduction methods for tactile sensing are appropriate for force sensing.

In the last three decades, computer vision has been extensively studied in many application areas which include character recognition, medical diagnosis, target detection, and remote sensing. The capabilities of commercial vision systems for robotic applications, however, are still limited. One reason for this slow progress is that robotic tasks often require sophisticated vision interpretation, yet demand low cost and high speed, accuracy, reliability, and flexibility. Factors limiting the commercially available computer vision techniques and methods to facilitate vision applications in robotics are highlights of the subsection on vision.

Resistive and Conductive Transduction 

This technique involves measuring the resistance either through or across the thickness of a conductive elastomer. As illustrated in Figure 14.5.1, the measured resistance changes with the amount of force applied to the materials, resulting from the deformation of the elastomer altering the particle density within it. Most commonly used elastomers are made from carbon or silicon-doped rubber, and the construction is such that the sensor is made up of a grid of discrete sites at which the resistance is measured.

A number of the conductive and resistive designs have been quite successful. A design using carbonloaded rubber originated by Purbrick at MIT formed the basis for several later designs. It was constructed

from a simple grid of silicon rubber conductors. Resistance at the electrodes was measured, which corresponds to loads. A novel variation of this design developed by Raibeit is to place the conductive sheet rubber over a printed circuit board (PCB) which incorporates VLSI circuitry, each forcel not only transduces its data but processes it as well. Each site performs transduction and processing operations at the same time as all the others. The computer is thus a parallel processor.

End Effector Design Issues

Good end effector design is in many ways the same as good design of any mechanical device. Foremost, it requires:

• A formal understanding of the functional specifications and relevant constraints. In the authors, experience, most design “failures” occurred not through faulty engineering, but through incompletely articulated requirements and constraints. In other words, the end effector solved the wrong problem.

• A “concurrent engineering” approach in which such issues as ease of maintenance, as well as related problems in fixturing, robot programming, etc., are addressed in parallel with end effector design.

• An attention to details in which issues such as power requirements, impact resistance, and sensor signal routing are not left as an afterthought. Some of the main considerations are briefly discussed below.

Sensing

Sensors are vital for some manufacturing applications and useful in many others for detecting error
conditions. Virtually every end effector design can benefit from the addition of limit switches, proximity sensors, and force overload switches for detecting improperly grasped parts, dropped parts, excessive assembly forces, etc. robot controller . The most complex class of sensors includes cameras and tactile arrays. A number of commercial solutions for visual and tactile imaging are available, and may include dedicated microprocessors and software.

These binary sensors are inexpensive and easy to connect to most industrial controllers. The next level of sophistication includes analog sensors such as strain gages and thermocouples. For these sensors, a dedicated microprocessor as well as analog instrumentation is typically required to interpret the signals and communicate with the

Although vision systems are usually thought of as separate from end effector design, it is sometimes desirable to build a camera into the end effector; this approach can reduce cycle times because the robot does not have to deposit parts under a separate station for inspecting them.
 
 Actuation

The actuation of industrial end effectors is most commonly pneumatic, due to the  availability of
compressed air in most applications and the high power-to-weight ratio that can be obtained. The grasp force is controlled by regulating air pressure.  The chief drawbacks of pneumatic actuation are the difficulties in achieving precise position control for active hands (due primarily to the compressibility of air) and the need to run air lines down what is otherwise an all-electric robot arm. Electric motors are also common. In these, the grasp force is regulated via the motor current. A  variety of drive mechanisms can be employed between the motor or cylinder and the gripper jaws, including worm gears, rack and pinion, toggle linkages, and cams to achieve either uniform grasping forces or a self-locking effect. For a comparison of different actuation technologies, with emphasis on servo-controlled appli- cations, see Hollerbach et al. (1992).

Fundamentals and Design Issues

A robot manipulator is fundamentally a collection of links connected to each other by joints, typically with an end effector (designed to contact the environment in some useful fashion) connected to the mechanism. A typical arrangement is to have the links connected serially by the joints in an open-chain fashion. Each joint provides one or more degree of freedom to the mechanism.

 

Manipulator designs are typically characterized by the number of independent degrees of freedom in the mechanism, the types of joints providing the degrees of freedom, and the geometry of the links connecting the joints. The degrees of freedom can be revolute (relative rotational motion θ between joints) or prismatic (relative linear motion d between joints). A joint may have more than one degree of freedom. Most industrial robots have a total of six independent degrees of freedom. In addition, most current robots have essentially rigid links (we will focus on rigid-link robots throughout this section).

Robots are also characterized by the type of actuators employed. Typically manipulators have hydraulic or electric actuation. In some cases where high precision is not important, pneumatic actuators are used.

 A number of successful manipulator designs have emerged, each with a different arrangement of joints and links. Some “elbow” designs, such as the PUMA robots and the SPAR Remote Manipulator System, have a fairly anthropomorphic structure, with revolute joints arranged into “shoulder,” “elbow,” and “wrist” sections. A mix of revolute and prismatic joints has been adopted in the Stanford Manipulator and the SCARA types of arms. Other arms, such as those produced by IBM, feature prismatic joints for the “shoulder,” with a spherical wrist attached. In this case, the prismatic joints are essentially used as positioning devices, with the wrist used for fine motions.

The above designs have six or fewer degrees of freedom. More recent manipulators, such as those of the Robotics Research Corporation series of arms, feature seven or more degrees of freedom. These arms are termed kinematically redundant, which is a useful feature as we will see later .

Key factors that influence the design of a manipulator are the tractability of its geometric (kinematic) analysis and the size and location of its workspace. The workspace of a manipulator can be defined as the set of points that are reachable by the manipulator (with fixed base). Both shape and total volume are important. Manipulator designs such as the SCARA are useful for manufacturing since they have a simple semicylindrical connected volume for their workspace (Spong and Vidyasagar, 1989), which facilitates workcell design. Elbow manipulators tend to have a wider volume of workspace, however the workspace is often more difficult to characterize. The kinematic design of a manipulator can tailor the workspace to some extent to the operational requirements of the robot.

In addition, if a manipulator can be designed so that it has a simplified kinematic analysis, many planning and control functions will in turn be greatly simplified. For example, robots with spherical wrists tend to have much simpler inverse kinematics than those without this feature. Simplification of the kinematic analysis required for a robot can significantly enhance the real-time motion planning and control performance of the robot system. For the rest of this section, we will concentrate on the kinematics of manipulators.

 For the purposes of analysis, a set of joint variables (which may contain both revolute and prismatic variables), are augmented into a vector q, which uniquely defines the geometric state, or configuration of the robot. However, task description for manipulators is most naturally expressed in terms of a different set of task coordinates. These can be the position and orientation of the robot end effector, or of a special task frame, and are denoted here by Y. Thus Y most naturally represents the performance of a task, and q most naturally represents the mechanism used to perform the task. Each of the coordinate systems q and Y contains information critical to the understanding of the overall status of the manipulator. Much of the kinematic analysis of robots therefore centers on transformations between the various sets of coordinates of interest.

Manipulator Kinematics

The study of manipulator kinematics at the position (geometric) level separates naturally into two subproblems: (1) finding the position/orientation of the end effector, or task, frame, given the angles and/or displacements of the joints (Forward Kinematics); and (2) finding possible angles/displacements of the joints given the position/orientation of the end effector, or task, frame  (Inverse Kinematics). At the  velocity level, the Manipulator Jacobian  relates joint  velocities to end effector  velocities and is important in motion planning and for identifying Singularities. In the case of Redundant Manipulators, the Jacobian is particularly crucial in planning and controlling robot motions. We will explore each of these issues in turn in the following subsections.