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Application of Artificial Intelligence Algorithms for Robot Development
Published in S. S. Nandhini, M. Karthiga, S. B. Goyal, Computational Intelligence in Robotics and Automation, 2023
R. M. Tharsanee, R. S. Soundariya, A. Saran Kumar, V. Praveen
The main components of a robot include arm or actuator, effector, sensor, controller and locomotive device. A robot arm also called a robot actuator is a series of joints which resembles the human arms. This arm is used to make interaction with the outside effectors. This can also be used to perform activities like painting, welding and serving. The effector is attached to the other end of the actuator which can perform the tasks as that of human arm and fingers. The locomotive device is actually a motor which can be used to provide power for the working of the robots. There are three types of power that can be provided by locomotor, namely electric, hydraulic (liquid power) and pneumatic (air/gas power). The controller is used to perform and monitor the tasks of the robot. The function of the controller is similar to that of a human brain. It also controls the robot at various levels. Sensors are used to sense the environmental conditions in order to make decisions and perform the task correctly. Figure 4.2 shows the general robot structure (see Figure 4.2).
Revolutionizing Manufacturing Using Cognitive IoT Technologies
Published in Pethuru Raj, Anupama C. Raman, Harihara Subramanian, Cognitive Internet of Things, 2022
Pethuru Raj, Anupama C. Raman, Harihara Subramanian
Industrial robots have tremendous potential to alter production processes comparable to the automation introduced by computers in offices. Some of the key benefits of using robots in factories are the following:Increase the speed of performing operationsIncrease the accuracy of performing an operationImprove the quality of tasks such as carrying heavy loads or weights by robots than by humansThese activities performed by robots have added tremendous value to manufacturing processes. One example could be the petrochemical industry which has used robots extensively to improve the safety and efficiency of performing operations that are otherwise very difficult to be done by humans. Some examples of such tasks are maintenance, inspection, repair, etc. The downside of using robots in some environments is that it could give rise to a breach of trust and accountability.
Introduction to Intelligent Robotic Systems
Published in Spyros G. Tzafestas, Intelligent Robotic Systems, 2020
The principal components of any robotic system are effectors (arms, hands, and legs), sensors (vision, touch or force, range, and acoustic), computers (local controllers, supervisors, and coordinators), and auxiliary equipment (end-arm tools, fixtures, pallets, conveyors, and others). Through appropriate combinations of these components an intelligent robot can perform tasks that need flexibility and artificial intelligence (i. e., perception, interpretation, and planning capabilities). Robotic systems may be classified in a sequence of increasing capability as follows: Teleoperated slave manipulatorLimited sequence manipulatorTeach-replay robotComputer-controlled robotIntelligent robot
If machines outperform humans: status threat evoked by and willingness to interact with sophisticated machines in a work-related context *
Published in Behaviour & Information Technology, 2023
Robots were designed to assist people, for example, to fulfill tasks at different workplaces (Broman and Finckenberg-Broman 2017), where they become more and more prominent (D’Cruz and Noronha 2021). In most use cases, robots are added to a workplace because they increase efficiency (Goštautaite et al. 2019) and safety (Borenstein 2011). Consequently, some human jobs may become redundant as the use of robots makes humans obsolete (McQuay 2018; Savela, Turja, and Oksanen 2018). By 2030, up to 20% of work could be done by robotic systems (Manyika et al. 2017). The past few years have already shown that the number of artificial intelligence and robot technologies in work environments is steadily increasing (Bankins and Formosa 2020) and was highlighted to be an important factor in a company’s success (Huang and Rust 2017; Weiss et al. 2011).
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.
Explainable AI for Security of Human-Interactive Robots
Published in International Journal of Human–Computer Interaction, 2022
Antonio Roque, Suresh K. Damodaran
Robots have been defined as “a system with sensors, actuators, and computing ability” (Archibald et al., 2017). There are many types of robots. For example, modern cars with autonomous features are a type of robot because “they are an example of a large complex system which can sense the environment (wheel speed, tire pressure, GPS location) and take actions (automatic braking, information display, unlocking car)” (Archibald et al., 2017). Robots are a type of Cyber-Physical System (CPS) (Clark et al., 2017), which are software embedded into a physical system that is used to control interactions with the physical world (Leccadito et al., 2018; Alguliyev et al., 2018; Ding et al., 2018; Greer et al., 2019). We will occasionally refer to CPSs in this article because there is a respectable amount of work on the safety and security of CPSs that could be applied to the special case of robots.