車床上料機械手設計（桂理工）

車床上料機械手設計（桂理工）,車床上料機械手設計（桂理工）,車床,機械手,設計,理工 本科畢業(yè)設計(論文) 外文翻譯（附外文原文） 學 院： 機械與控制工程 課題名稱： 車床上料機械手設計 專業(yè)(方向)： 機械設計制造及其自動化 班 級： 機械11級2班 學 生： 梁學念 指導教師： 孫金榮 日 期： 2015年3月12日 21 外文原文： Mechanical and control system for Manipulators Abstract: Recently, in the world with a clip or a hand robot system has been developed, a variety of methods is applied on the, quasi humanized and non-personification. Not only the mechanical structure of these systems is investigated, but also the necessary control system is also included.. As the staff, these robots can use their hands to grasp different objects, without changing the clip. These manipulators possess special athletic abilities (such as small mass and inertia), which enable the object to be more complex and more precise in the work of robot manipulators.. These complex operations are grasped around arbitrary angle and axis rotation.. This paper outlines the general design of this manipulator, and gives a sample of such manipulators, such as the Karlsruhe smart hand. At the end of this paper, some new ideas are introduced, such as the use of liquid actuators for humanoid robot design a brand new robot manipulator. Keywords: multi robot manipulator; robot hand; finishing operation; mechanical system; control system 1 .Introduction In June 2001 in Karlsruhe, Germany to carry out special study a humanoid robot, in order to develop in a normal environment (such as kitchen or the living room) and human cooperation and interaction of the robot system. The design of these robots is designed to help us capture objects of size, shape and weight in a non -professional, non - industrial condition, such as in many objects. At the same time, they must be able to manipulate the object very well. This flexibility can only be through a strong adaptability of robot hand grasping system to obtain, that is, the so-called multi refers to the robot or robot hand. The research project mentioned above is to create a humanoid robot, which will equip this robot hand system.. This novice will be produced by two organizations, which are IPR (process control and Robotics Research Institute) and C (Computer Science Institute), University of Karlsruhe.. These two organizations have the experience of making such systems, but slightly different views. IPR made Karlsruhe dexterous hand II (as shown in Figure 1), is a four finger gripper is independent of each other, we will be introduced in detail in this paper. The hand made by IAI (as shown in Figure 17) is used as prosthetic for the disabled. Figure 1.IPR Karlsruhe smart hand Figure 2 fluid hand developed by IAI 2 .general structure of robot hand A robot hand can be divided into two major subsystems: mechanical systems and control systems. The mechanical system can be divided into the structure design, the drive system and the sensor system, we will further introduce in the third part. In the fourth part of the introduction of the control system at least by the control of hardware and software components. We will be on the two system problems of a basic introduction, and then use the Karlsruhe dexterous hand II demonstration. 3 .Mechanical Systems The mechanical system will describe how the hand looks and what components. It determines the structure design, the number of fingers and the use of materials. In addition, the position of the actuator (such as the motor) and the sensor (e.g. position encoder) is also determined. 3.1 structure design The structure design will have the very important function to the manipulator's flexibility, namely it can grasp which kind of object and can carry on to the object to carry on what kind of operation. When designing a robot hand, three basic elements must be determined: the number of fingers, the number of fingers, the size and placement of the fingers.. In order to crawl and operate the object safely within the manipulator, at least three fingers. In order to operate the object being grasped for 6 degrees of freedom (3 translational and 3 rotational degrees of freedom), each finger must have 3 separate joints.. This method was used in the first generation of Karlsruhe's smart hand.. However, in order to catch an object without the need to release it first to pick up, at least 4 fingers. Two methods: the human and the non - human are to determine the size and placement of the finger.. Then it will depend on the object and the type of operation to which the desired operation is selected. It is easy to transfer grasping intention from hand to robot hand.. However, the placement of different sizes and asymmetric positions of each finger will increase the processing cost, and it is the control system becoming more complicated, because each finger must be controlled separately. For the symmetrical arrangement of identical fingers, often using a non-anthropomorphic approach. Because only need to process and construct a single "finger module", it can reduce the processing cost, but also the control system is simplified. 3.2 drive system The flexibility of the actuator is also greatly affected by the drive of the joints, because it determines the potential strength, precision and speed of the joint movement.. Two aspects of the mechanical movement need to be considered: the movement source and the movement direction. In this case, there are several different methods, such as the paper [3], which can be produced by hydraulic cylinders or pneumatic cylinders, or, as most of the case, the motor is used.. In most cases, motor drive, such as motor too big and not directly associated with the corresponding finger joint together. Therefore, the movement must by the driver (usually located on the machine arm last connection point) transferred. There are several ways to realize this movement, such as the use of keys, the drive belt and the active axis. Using the indirect drive method of finger joint, more or less reduces the strength and accuracy of the whole system, and at the same time, the control system is complicated, because of different joint of each finger is often mechanically even together, but in the software of the control system but are respectively independent control. Because of these shortcomings, the direct fusion of the small motor drive and the knuckle is quite necessary. 3.3 sensing system The sensing system of the robot hand can transfer the feedback information from the hardware to the control software.. It is necessary to establish a closed loop control for finger or object.. 3 types of sensors were used in the machine. 1）Hand state sensors determine the position of fingertip and finger joint and finger force situation. Know the precise position of the fingertips will make precise control possible. In addition, knowing that the finger is the force that is grasped at the object, you can grab a fragile object without breaking it. 2）The grasping state sensor provides the contact information between the finger and the object. This kind of tactile information can be determined in the process of grasping the first contact with the object in time, and can also avoid incorrect grasping, such as the edge and tip of the object.. It can also detect whether the object has been caught, so as to avoid the object due to fall and damage. 3）The object or pose sensor is used to determine the shape, position and direction of the object in a finger. This sensor is very essential if it is not clear to the case of the object.. If this sensor can also act on the object that has been grasped, it can also control the pose (position and direction) of the object, thus monitoring whether or not. Depending on the drive system, the geometrical information about the joint position can be measured at a motion drive or directly at the joint. For example, if there is a rigid shaft coupling between the motor and the knuckle, then the position of the joint can be measured by a motor shaft (before the gear or after the gear).. However, if this coupling stiffness is not enough or to get a high accuracy, it can not use this method. 3.4 the mechanical system of the robot hand in Karlsruhe In order to obtain more complex operation such as heavy grasping, the Karlsruhe smart hand II (KDH II) is composed of 4 fingers, and each finger is composed of 3 independent joints.. The hand is designed for applications in industrial environments (Figure 3) and a control box, cylinder and screw nut and other objects. Therefore, we selected four identical fingers. They are symmetric, non-anthropomorphic configuration and each finger can rotate 90 DEG (Fig. 4). View from the first generation of Karlsruhe dexterous hand design by experience, for example, the problem of mechanical caused by the drive belts and larger friction factor leading to the control problem of Karlsruhe dexterous hand II uses a number of different design decisions. The DC motor between the joint 2 and the joint of each finger is integrated into the anterior part of the finger (Figure 5).This arrangement can be used with hard ball gears to transmit motion to the joints of the fingers. In the motor shaft angle encoder (before the gear) can be used as a high precision position sensor. Figure 3 KDH II on industrial robot Figure 4 KDH II top view In order to perception of the role of finger force on the object, we invented a six axis force torque sensor (Figure 6). The sensor can be used as a fingertip for the end of a finger and is equipped with a spherical fingertip.. It can grab lighter objects, but also can grab 3-5kg similar heavier objects. This sensor can measure the force of the direction of X, Y and Z and the torque of the winding axis.. In addition, the laser triangulation sensor 3 collinear is placed in the hands of KDH II (Figure 5). Because there are 3 such sensors, therefore not only can measure the distance between 3 single points, if you know the shape of the object, but also can detect the distance between the object surface and direction. The working frequency of the object state sensor is 1kHz, which can detect and avoid the slide of the object Figure 5 KDH II side view. Figure six a 6 degree of freedom torsion sensor with a strain gage sensor 4 control system The robot's control system determines which potential dexterity skills can actually be used, and those skills are provided by mechanical systems.. As mentioned before, the control system can be divided into the control computer, namely, the hardware and the control algorithm is the software. The control system must meet the following conditions: 1) Must have sufficient input and output ports. For example, a low level hand with 9 degrees of freedom, its drive needs at least 9 way to simulate the output port, and there are 9 paths from the angle encoder input port. Such as force sensor, tactile sensor and object sensor, then port number will be increased by several times. 2) The ability to have a quick and real-time response to external events. For example, when the detected object falls, the corresponding measures can be taken immediately. 3) With a higher computational power to address some of the different tasks. Such as path planning, coordinate conversion, and closed-loop control for multi - object and object - parallel execution. 4) The volume of the control system is small so that it can be integrated directly into the operating system.. 5) In the control system and between the drive and sensor must be electrically short. Especially for the sensor, if there is no word, a lot of interference will interfere with the sensor signal. 4.1 control hardware In order to meet the requirements of the system, the hardware is distributed in several special processors.. The controller can be easily integrated into the operating system, such as the low input output interface (motor and sensor), which is handled by a simple microcontroller.. However, the higher level of the control port requires a higher computing power, and a flexible real-time operating system is needed.. This can be easily resolved through the PC. Therefore, the control hardware is often composed of a distributed computer system, which is a microcontroller, and the other is a powerful processor. Different computing units are connected by a communication system, such as bus system. 4.2 control software Robot hand control software is quite complex. Must be real-time and parallel control of the fingers, but also plan the new trajectory of the fingers and objects. Therefore, in order to reduce the complexity of the problem, it is necessary to divide this problem into several sub problems to deal with.. On the other hand, software development.. Robot hand is a research project, its programming environment such as user interface, programming tools and debugging facilities must be very strong and flexible. These can only be met using a standard operating system. The hierarchical control system method is widely used in the robot after pruning, in order to meet the special requirements of the manipulator control. 4.3 control system of the robot hand in Karlsruhe As said in Section 4.1, a distributed method (Figure 7) is adopted for the hardware of the control hardware of the smart hand of Karlsruhe.. A microcontroller controls a finger drive and sensor respectively, and a microcontroller is used to control the object state sensor (laser triangulation).. These microcontrollers (Figure 7 the left and right side of the box) are directly mounted on the hand, so the shorter electrical connection between the driver and the sensor can be guaranteed. These microcontrollers are connected with the master computer and the master computer.. This master computer (Figure 8, gray box in Figure 7) is a parallel computer composed of six industrial computers. These computers are arranged in a two-dimensional plane. Adjacent computer module (a computer with up to 8 adjacent modules) using the dual port RAM for rapid communication (Figure 7, the dark gray box). A computer used to control a finger. Another is used to control the position between the object sensor and the object.. The rest of the computer is safely around the computer as mentioned above.. These computers are used to coordinate the entire control system. The structure of the control software reflects the architecture of the control hardware.. As shown in Figure 9. Figure 7 II KDH control hardware architecture Figure 8 parallel master computer for controlling II KDH A three maximum levels of online planning regarding this hand control system are being planned. The ideal object displacement command can be obtained by the superior robot control system and can be used as the precise programming of the object path.. According to the target path, the feasible fetching behavior of the finger can be planned (the feasible grasping position of the object) is feasible.. Now that the object movement plan can be obtained by finger path planning, and the real-time capability of the system is transmitted to the system.. If an object is grasped, its movement path is passed to the object's state controller.. This controller controls the pose of an object, which is determined by the sensor of the finger and the object state, and is used to obtain the desired pose.. If a finger does not touch the object, its mobile path will pass directly to the hand controller.. This hand controller will be associated with the expected finger position to all fingers of the controller to coordinate motion of all fingers. These are driving finger drives with the help of finger sensors. Figure 9 hand control system for KDH II5 experimental results To verify the ability of the Karlsruhe smart hand, we chose two requirements for operation.. One problem is the control of the pose (position and direction) of the object under the influence of the Internet.. Another problem is that the object must be able to rotate around any angle, which can only be realized by heavy catch.. This can reflect the operation ability of the complex task of the robot hand in Karlsruhe.. 5.1 object attitude control The object of the attitude controller is to determine the position and direction of the object to fit the given trajectory.. This task must be obtained in real-time conditions, despite the presence of internal changes and external disturbances.. Internal changes such as the rolling of the ball fingers on the object when the object is moving. This situation is shown in Figure 10, figure 11. This will cause unwanted additional movement and tilt of the object. The pose of these errors is hard to estimate.. Therefore, the input of the object state sensor must modify these errors. For the Karlsruhe smart hand, the three laser triangulation sensor is used to correct this error.. Figure 12 shows the tilt of the object in Figure 9 without attitude control.. The chart shows the expected trajectory in the X direction over time, while the image shows the actual rotation of the object (tilt) results. Because the object is enabled, the object in Figure 13 is reduced greatly.. The rotation of the object above remains constant, as expected Figure 10 additional displacement due to rolling Figure 12 No state controlled object tilt Figure 11 an additional undesired tilt due Figure 13 object state control to reduce to the rolling of a ball finger tip over an object the object Tilt The object state controller is also necessary for the compensation of external interference.. For example, the robot (arm, hand or finger) or the collision between objects and the outside may cause the slide of the object. This is more likely to lead to the loss of the object, which is not the case. In order to avoid the loss of an object in this case, it is necessary to detect the slide of the object and act quickly to stabilize the object.. In order to validate the Karlsruhe dexterous hand II control system of this interference processing capability, we do the following experiments: object to be caught, the finger contact force constant is reduced until the object began to fall. After the laser triangulation sensor detects the slide, the object state controller takes measures to re regulate the object to the desired position.. Figure 15 shows an example of this experiment.. In particular, Figure 14, which shows that the object falls off the start of the quite sudden and fairly fast. But the object state controller can also quickly enough to detect and compensate for slip, the position of the object (here: especially in X direction is sliding direction and the object's direction to and the beginning of the expected soon more consistent results. Figure 14: the actual object position of the X direction Figure 15 slide experiment: the actual object direction of the Z axis 5.2 catch Although the Karlsruhe smart hand is very flexible, it can not get every ideal object manipulation in the first operation.. This stems from the fact that fingers are small relative to the normal industrial robot, so the working range is very limited.. If the object is caught by fingers, it can be manipulated for the first time in the remainder of all fingers.. The condition of the feasible operation is that all the contact points must be in the working range of the associated finger for a long time. This greatly limits the feasibility of the operation.. In order to overcome this limitation, a operation called heavy grasping must be executed. When a contact point reaches the restricted area of the associated finger, the finger must be detached from the object and moved to a new contact position.. It must be more than 3 fingers to make the operation reliable. The period