This article is focused on enhancement of HW/SW device by cooperation with a smartphone interface. The device was a programmable Lego Mindstorms Education EV3 set in the form of a robot designed to solve the Rubik’s Cube. The aim of the research was to replace the built-in color sensor with a camera that would allow the cube scanning process to be accelerated. Two approaches were chosen to meet the goal: the NXTcam camera, accessible as an accessory to expand the set, and the camera built into the smartphone. The use of NXTcam led to better scan time, but this result was prone to external influences. The camera on the smartphone sped up the scanning process to 57% of the original time. The impact of external factors on the outcome was significantly lower, compared to NXTcam. In the experiment, the cube solving process was observed in natural light, with addition distractive light source and in artificial light.
Data Matrix codes can be a significant factor in increasing productivity and efficiency in production processes. An important point in deploying Data Matrix codes is their recognition and decoding. In this paper is presented a computationally efficient algorithm for locating Data Matrix codes in the images. Image areas that may contain the Data Matrix code are to be identified firstly. To identify these areas, the thresholding, connected components labelling and examining outer bounding-box of the continuous regions is used. Subsequently, to determine the boundaries of the Data Matrix code more precisely, we work with the difference of adjacent projections around the Finder Pattern. The dimensions of the Data Matrix code are determined by analyzing the local extremes around the Timing Pattern. We verified the proposed method on a testing set of synthetic and real scene images and compared it with the results of other open-source and commercial solutions. The proposed method has achieved better results than competitive commercial solutions.
Currently, the topic of automation of logistic processes in warehouses is relevant. The article considers a control system of high level for a mobile robot with a differential drive with a maximum payload of 200 kg with motion simulation in the Matlab Simulink software product. Optimal control of drives based on brushless DC motors at the lower level has been developed. The transient time of low level control system is 1.067 seconds. The mobile robot control system in the minimum version consists of ten ultrasonic distance sensors located along the perimeter of the mobile robot body and of eight contrast band sensors.
The development of scientific and technical progress in measuring and microprocessor technology, advances in artificial intelligence methods give impetus to the development of technical diagnostics of mechatronic systems. In mechatronic systems, electrical drives are based on asynchronous motors, DC motors, synchronous and stepper motors, and mechanical drives are based on gearboxes. Failure of motors and gearboxes leads to equipment shutdown, continuous production and financial losses of the company. Therefore, tools are needed to monitor the current status of devices.
PL
Rozwój postępu naukowo-technicznego w dziedzinie techniki pomiarowej i mikroprocesorowej, postęp w metodach sztucznej inteligencji dają impuls do rozwoju diagnostyki technicznej systemów mechatronicznych. W systemach mechatronicznych napędy elektryczne bazują na silnikach asynchronicznych, silnikach prądu stałego, silnikach synchronicznych i krokowych, a napędy mechaniczne bazują na przekładniach. Awaria silników i przekładni prowadzi do zatrzymania urządzeń, ciągłej produkcji i strat finansowych firmy. Dlatego potrzebne są narzędzia do monitorowania bieżącego stanu urządzeń..
In the paper we deal with optimization of manipulation logistics using Data Matrix codes. Our goal is scanning and decoding Data Matrix codes in real-time. We have designed and verified an efficient computer aided method for location of the Data Matrix codes. This method is also suited to real-time processing and has been verified on a test set of images taken from real industrial world. We have proposed a modified, computationally efficient local thresholding technique that uses local mean and variation under the sliding window. The proposed Data Matrix code localization algorithm utilizes the connecting of the adjoining points into the continuous regions and determining of the boundaries of the outer region and it works in two basic steps: localization of the Finder Pattern and verification of the Timing Pattern. Part of the algorithm deals also with the decoding of the Data Matrix code using external libraries. Data Matrix codes can be used to mark logistic units, parts, warehousing positions, but also for automated robot navigation. Because of their low cost, accuracy, speed, reliability, flexibility and efficiency, as well as the ability to write large amounts of data on a small area, they still have a great advantage in logistics.
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