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Types of Robols and Their Integration into Computer-Integrated Manufacturing Systems
Published in Ulrich Rembold, Robot Technology and Applications, 2020
An industrial robot is a general-purpose machine that is programmable and performs skillfully manipulation tasks. It is designed as a programmable, multifunctional manipulator to handle materials, parts, tools, or special devices in various manufacturing operations. In some cases a robot may have locomotive capabilities. Figure 1.1 shows several robot configurations conceived for manipulation, locomotion, or both. A robot consists of the kinematic and mechanical system, motor drives, axis servo control, sensors, and end-effector, workcell control, and the programming software. In CIM a more generalized view of a robot system is used. Several levels of control processing data with different degrees of abstraction are part of the generalized robot system, namely the manipulator, robot, cell, shop floor, and in some cases the factory control levels. Product design, manufacturing planning, and programming must consider each control level. The various supporting tools of these activities and their integration into an overall system are described in the chapters of this book.
Applications of Technology
Published in Roger Timings, Basic Manufacturing, 2006
There are two main types of industrial robot. The general-purpose robot possessing certain anthropomorphic (human-like) characteristics. The most anthropomorphic characteristic of an industrial robot is its arm and wrist. This combination of arm and wrist together with the capability of the robot to be programmed, makes it ideally suited to a variety of production tasks, including machine loading and unloading, welding, spray painting and assembly. The robot can be programmed to perform a sequence of mechanical motions, and it can repeat that motion sequence indefinitely until reprogrammed to perform some other task.The pick and place dedicated robot is less complex and is made up of standard components to perform a specific task. It costs a great deal less than the general-purpose robot and is also much more accurate. It is usually driven by a PLC. An example of a pick and place robot is considered in case study 4.10.
Protopian Un-forecast
Published in Chace Calum, Artificial Intelligence and the Two Singularities, 2018
2.Manufacturing: Industrial robots are cheap enough, and easy enough to programme and maintain, that manufacturers normally choose to buy a robot rather than hire a human when they expand a line. The most sophisticated manufacturers of cars and electrical equipment now have a few ‘lights-out’ factories where no humans are normally required, but this is still rare. Likewise, although a few manufacturers have laid off large numbers of workers, most have yet to make this step, relying instead on natural wastage to reduce costs.
Towards gestured-based technologies for human-centred Smart Factories
Published in International Journal of Computer Integrated Manufacturing, 2023
Vito Modesto Manghisi, Markus Wilhelm, Antonello Uva, Bastian Engelmann, Michele Fiorentino, Jan Schmitt
The capture of movements can additionally be used for interaction between humans and machines to provide an intuitive process by using gesture control. This allows a modification of existing production systems by new and smart interaction mechanisms. An obvious application for gesture commands is the control of robots. Industrial robots are especially used to assist humans in working environments, e.g. due to dangerous environmental conditions or high physical loads. Due to the fact that a robot is supposed to replace the movements of an employee, programming through corresponding movements is an intuitively applicable method. In the following Table 3, a review of gesture-based robot control is presented. The utilized technologies, the type of robot and the kind of control gestures are classified. The technologies are divided into four categories: wearables, camera, infrared camera (Leap Motion) and depth camera (Microsoft Kinect). The robot types are classified into professional industrial robots and non-professional/commercial robots, which functionalities are similar to industrial robots. Other areas with strong research activity in gesture control, such as humanoid robots, are left out. A distinction is made between static gestures and dynamic gestures. Static gestures are firmly assigned gestures that trigger exactly one movement in the robot. Dynamic gestures can be the indirect transmission of motion sequences, e.g. the movements of a human hand on a robot arm. Mirroring, in our context, means transmitting the (scaled) spatial coordinates of the arm movement, and thus, determining the position of the end effector.
Image space trajectory tracking of 6-DOF robot manipulator in assisting visual servoing
Published in Automatika, 2022
Megha G. Krishnan, Ashok Sankar
The requirement for automated industrial operations is driving up the demand for robots in manufacturing industries. Industrial robots, mainly robot manipulators play a key role in industrial automation. Robotic manipulators have been used in various industrial applications like spot welding, material handling, pick & place and many more. It requires high endurance, speed and meticulousness. However, the application of manipulators in industries is limited by their lack of intelligence to take decisions. To overcome this problem, a vision sensor is integrated into the robot control systems. This provides a better operation and aids the robot to navigate the landscape and avoid collisions. In visual servoing, the data acquired from the vision sensors are used to control the motion of a robot. Mathematically, the error between the desired and actual visual features is minimized. On the other hand, the loss of data while projecting the 3D information onto a 2D image plane in the camera is a challenge in vision-based control. Moreover, the non-linearities and complex structure of a manipulator robot make the problem more complex [1].
An indirect method of industrial robot programming for machining tasks based on STEP-NC
Published in International Journal of Computer Integrated Manufacturing, 2019
Nikola Slavkovic, Sasa Zivanovic, Dragan Milutinovic
Compared to machine tools, industrial robots are cheaper and more flexible with potentially larger work space (Abele, Kulok, and Weigold 2005; Pan and Zhang 2008). It is for these reasons that industrial robots are identified as successful cost-effective and flexible alternative to multi-axis machine tools for some machining tasks. These include milling materials, such as clay, foam, wax, etc. for new product design, styling, and rapid prototyping projects. Machining of work pieces from traditional materials, such as wood, stone, aluminium, etc. in which dimensional tolerances are low or even middle also produce satisfactory results (Shin-Ichi et al. 1999; Abele, Kulok, and Weigold 2005; Abele, Weigold, and Rothenbucher 2007). The poor accuracy, stiffness and complexity of programming are the most important limiting factors for wider adoption of robotic machining in machine shops (Abele, Weigold, and Rothenbucher 2007). The robot programming complexity is indicated as a major limiting factor for using robot in machining tasks (Chen and Hu 1999; DePree and Gesswein 2008; Pan and Zhang 2008; Milutinovic et al. 2011). This work deals only with the issue of industrial robot programming for machining tasks based on STEP-NC, while the problem of accuracy and compliance of the robot for machining is discussed in the works by Slavkovic et al. (2013) and Slavkovic, Milutinovic, and Glavonjic (2014). These papers also report the developed off-line method for machining error compensation induced by cutting forces due to robot compliance.