New cognitive info-communication channels for human-machine interaction

The main goal of this paper is to discuss a new paradigm for robot teaching and supervising which is based on cognitive info-communication channels for human-machine interaction. According to the studied concept the robot is considered as an unskilled worker “who” (which) is strong and capable for precise manufacturing. “He” (it) has a special kind of intelligence, but “he” is handicapped in some senses, that is why “he” needs special treatment. We must command “him” clearly in a special way and we must supervise “his” work. If we can elaborate a proper way for communicating with this “new worker”, as an additional dimension of robotization, we can get a capable new “colleague”. The ultimate goal is to help the boss to be able to give the daily task to a robot in a similar way as he/she able to give the jobs to the human workers. For example, by providing the CAD documentation with some additional verbal explanation

Overview of modern teaching equipment that supports distant learning

Laboratory is a key element of engineering and applied sciences educational systems. With the development of Internet and connecting IT technologies, the appearance of remote laboratories was inevitable. Virtual laboratories are also available; they place the experiment in a simulated environment. However, this writing focuses on remote experiments not virtual ones. From the students’ point of view, it is a great help not only for those enrolling in distant or online courses but also for those studying in a more traditional way. With the spread of smart, portable devices capable of connection to the internet, students can expand or restructure time spent on studying. This is a huge help to them and also allows them to individually divide their time up, to learn how to self-study. This independent approach can prepare them for working environments. It offers flexibility and convenience to the students. From the universities’ point of view, it helps reduce maintenance costs and universities can share experiments which also helps the not so well-resourced educational facilities

Bacterial Memetic Algorithm Trained Fuzzy System-Based Model of Single Weld Bead Geometry

This article presents a fuzzy system-based modeling approach to estimate the weld bead geometry (WBG) from the welding process variables (WPVs) and to achieve a specific weld bead shape. The bacterial memetic algorithm (BMA) is applied to solve these problems in two different roles, as a supervised trainer, and as an optimizer. As a supervised trainer, the BMA is applied to tune two different WBG models. The bead geometry properties (BGP) model follows a traditional approach providing the WBG properties as outputs. The direct profile measurement (DPM) model describes the bead profiles points by a non-linear function realized in the form of fuzzy rules. As an optimizer, the BMA utilizes the developed fuzzy systems to find the solution sets of WPVs to acquire the desired WBG. The best performance is achieved by applying six rules in the BGP model and eleven rules in the DPM model. The results indicate that the normalized root means square error for the validation data set lies in the range of 0:40 - 1:56% for the BGP model and 4:49 - 7:52% for the DPM model. The comparative analysis suggests that the BGP model estimates the BWG in a superior manner when several WPVs are altered. The developed fuzzy systems provide a tool for interpreting the effects of the WPVs. The developed optimizer provides multiple valid set of WPVs to produce the desired WBG, thus supporting the selection of those process variables in applications

Bead geometry modeling on uneven base metal surface by fuzzy systems for multi-pass welding

This paper presents a modeling method of weld bead profiles deposited on uneven base metal surfaces and its application in multi-pass welding. The robotized multi-pass tungsten inert gas welding requires precise positioning of the weld beads to avoid welding defects and achieve the desirable welding join since the weld bead shapes depend on the surface of the previously deposited beads. The proposed model consists of fuzzy systems to estimate the coefficients of the profile function. The characteristic points of the trapezoidal membership functions in the rule bases are tuned by the Bacterial Memetic Algorithm during supervised training. The fuzzy systems are structured as multiple-input-single-output systems, where the inputs are the welding process variables and the coefficients of the shape functions of the segments underlying the modeled bead; the outputs are the coefficients of the bead shape function. Each segment surface is approximated by a second-order polynomial function defined in the weld bead’s local coordinate system. The model is developed from empirical data collected from single and multi-pass welding. The performance of the proposed model is compared with a multiple linear regression model. During the experimental validation, first, the individual beads are evaluated by comparing the estimated coefficients of the profile function and other bead characteristics (bead area, width, contact angles, and position of the toe points) with the measurements, and the estimations of a multiple linear regression model. Second, the sequential placement of the weld beads is evaluated while filling a straight Vgroove by comparing the estimated bead characteristics with the measurements and calculating the accumulated error of the filled groove cross-section. The results show that the proposed model provides a good estimation of the bead shapes during deposition on uneven base metal surfaces and outperforms the regression model with low error in both validation cases. Furthermore, it is experimentally validated that the derived bead characteristics provide a suitable measure to identify locations sensitive to welding defects

New cognitive info-communication channels for human-machine interaction

The main goal of this paper is to discuss a new paradigm for robot teaching and supervising which is based on cognitive info-communication channels for human-machine interaction. According to the studied concept the robot is considered as an unskilled worker “who” (which) is strong and capable for precise manufacturing. “He” (it) has a special kind of intelligence, but “he” is handicapped in some senses, that is why “he” needs special treatment. We must command “him” clearly in a special way and we must supervise “his” work. If we can elaborate a proper way for communicating with this “new worker”, as an additional dimension of robotization, we can get a capable new “colleague”. The ultimate goal is to help the boss to be able to give the daily task to a robot in a similar way as he/she able to give the jobs to the human workers. For example, by providing the CAD documentation with some additional verbal explanation

Overview of modern teaching equipment that supports distant learning

Laboratory is a key element of engineering and applied sciences educational systems. With the development of Internet and connecting IT technologies, the appearance of remote laboratories was inevitable. Virtual laboratories are also available; they place the experiment in a simulated environment. However, this writing focuses on remote experiments not virtual ones. From the students’ point of view, it is a great help not only for those enrolling in distant or online courses but also for those studying in a more traditional way. With the spread of smart, portable devices capable of connection to the internet, students can expand or restructure time spent on studying. This is a huge help to them and also allows them to individually divide their time up, to learn how to self-study. This independent approach can prepare them for working environments. It offers flexibility and convenience to the students. From the universities’ point of view, it helps reduce maintenance costs and universities can share experiments which also helps the not so well-resourced educational facilities