Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

High-Speed Vision and Force Feedback for Motion-Controlled Industrial Manipulators

Over the last decades, both force sensors and cameras have emerged as useful sensors for different applications in robotics. This thesis considers a number of dynamic visual tracking and control problems, as well as the integration of these techniques with contact force control. Different topics ranging from basic theory to system implementation and applications are treated. A new interface developed for external sensor control is presented, designed by making non-intrusive extensions to a standard industrial robot control system. The structure of these extensions are presented, the system properties are modeled and experimentally verified, and results from force-controlled stub grinding and deburring experiments are presented. A novel system for force-controlled drilling using a standard industrial robot is also demonstrated. The solution is based on the use of force feedback to control the contact forces and the sliding motions of the pressure foot, which would otherwise occur during the drilling phase. Basic methods for feature-based tracking and servoing are presented, together with an extension for constrained motion estimation based on a dual quaternion pose parametrization. A method for multi-camera real-time rigid body tracking with time constraints is also presented, based on an optimal selection of the measured features. The developed tracking methods are used as the basis for two different approaches to vision/force control, which are illustrated in experiments. Intensity-based techniques for tracking and vision-based control are also developed. A dynamic visual tracking technique based directly on the image intensity measurements is presented, together with new stability-based methods suitable for dynamic tracking and feedback problems. The stability-based methods outperform the previous methods in many situations, as shown in simulations and experiments

Advanced teleoperation and control system for industrial robots based on augmented virtuality and haptic feedback

There are some industrial tasks that are still mainly performed manually by human workers due to their complexity, which is the case of surface treatment operations (such as sanding, deburring, finishing, grinding, polishing, etc.) used to repair defects. This work develops an advanced teleoperation and control system for industrial robots in order to assist the human operator to perform the mentioned tasks. On the one hand, the controlled robotic system provides strength and accuracy, holding the tool, keeping the right tool orientation and guaranteeing a smooth approach to the workpiece. On the other hand, the advanced teleoperation provides security and comfort to the user when performing the task. In particular, the proposed teleoperation uses augmented virtuality (i.e., a virtual world that includes non-modeled real-world data) and haptic feedback to provide the user an immersive virtual experience when remotely teleoperating the tool of the robot system to treat arbitrary regions of the workpiece surface. The method is illustrated with a car body surface treatment operation, although it can be easily extended to other surface treatment applications or even to other industrial tasks where the human operator may benefit from robotic assistance. The effectiveness of the proposed approach is shown with several experiments using a 6R robotic arm. Moreover, a comparison of the performance obtained manually by an expert and that obtained with the proposed method has also been conducted in order to show the suitability of the proposed approach

Fragmentation, income, gender and poverty linkages: The case of the Maquila Industry in Guatemala

This article addresses the participation of Guatemala in the world apparel chain of production and its likely impact on income, gender and poverty levels. Making use of household survey data from Guatemala, the study relies on matching techniques for analyzing changes on labour earnings in the assembly industry with special emphasis on female workers. The evidence suggests that maquila-based employees are, on average, better paid than those occupied in the reserve sector, however, the former group seems to be exposed to a less favourable working environment when compared to those employed in other manufacturing industries. Moreover, the study reveals huge income disparities in terms of gender, exacerbated, among others, by the typical patriarchal structure prevailing in the Guatemalan economy. Our results introduce reservations on the role played by the maquila model, calling for a reassessment of its likely poverty reduction effect in Guatemala.

Dynamic simulator for a grinding circuit

Thesis (M.S.) University of Alaska Fairbanks, 2017The grinding circuit is a primary and indispensable unit of a mineral processing plant. The product from a grinding circuit affects the recovery rate of minerals in subsequent downstream processes and governs the amount of concentrate produced. Because of the huge amount of energy required during the grinding operation, they contribute to a major portion of the concentrator cost. This makes grinding a crucial process to be considered for optimization and control. There are numerous process variables that are monitored and controlled during a grinding operation. The variables in a grinding circuit are highly inter-related and the intricate interaction among them makes the process difficult to understand from an operational viewpoint. Modeling and simulation of grinding circuits have been used by past researchers for circuit design and pre-flowsheet optimization in terms of processing capacity, recovery rate, and product size distribution. However, these models were solved under steady approximation and did not provide any information on the system in real time. Hence, they cannot be used for real time optimization and control purposes. Therefore, this research focuses on developing a dynamic simulator for a grinding circuit. The Matlab/Simulink environment was used to program the models of the process units that were interlinked to produce the flowsheet of a grinding circuit of a local gold mine operating in Alaska. The flowsheet was simulated under different operating conditions to understand the behavior of the circuit. The explanation for such changes has also been discussed. The dynamic simulator was then used in designing a neural network based controller for the semi-autogenous mill (SAG). A two-layer non-linear autoregressive (NARX) neural network with feed to the mill as exogenous input was designed using data generated by the simulator for a range of operating conditions. Levenberg-Marquardt (LM) and Bayesian Regularization (BR) training algorithms were used to train the network. Comparison of both algorithms showed LM performed better provided the number of parameters in the network were chosen in a prudent manner. Finally, the implementation of the controller for maintaining SAG mill power to a reference point is discussed

Study of experimental modal analysis method of machine tool spindle system

Dynamic properties of the machine tools especially the spindle systems contribute greatly to the reliability of the machine tools. The increasing use of modal analysis as a standard tool to estimate the dynamic modal parameters means that both experienced and inexperienced analysts are faced with new challenges: uncertainty about the accuracy of results. Therefore, the key requirement for experimental modal analysis is a reliable, efficient and accurate experimental method in spindle system analysis. Several processes, such as reference and response selection in modal test however would make the system identification process for structural dynamics inaccurate. To investigate the results accuracy when applying experimental modal analysis on machine tool spindle, this work hence further studied the experimental setup itself based on the reference and response selection. The reference selection and reference optimization method is developed for the accuracy and efficiency improving purpose. First, by comparing results from different reference quantity and direction test, the method to select reference points is studied. Then the modal parameters are verified by the complex mode indicator functions and finite element analysis to study the influence of the reference on the modal analysis accuracy. Next, improved algorithm of response points optimization is developed based on the MAC matrix to minimize the number and location of measuring response points. Lastly, the general standard and method to select the reference and response points are put forward. The approach setting-up the experimental impact test provides reliable and accurate results and can reduce the testing time at the same time