Location and Position Determination Algorithm For Humanoid Soccer Robot

The algorithm of location and position determination was designed for humanoid soccer robot. The robots have to be able to control the ball effectively on the field of Indonesian Robot Soccer Competition which has a size of 900 cm x 600 cm. The algorithm of location and position determination uses parameters, such as the goalpost’s thickness, the compass value, and the robot’s head servo value. The goalpost’s thickness is detected using The Centre of Gravity method. The width of the goalpost detected is analyzed using the principles of camera geometry to determine the distance between the robot and the goalpost. The tangent value of head servo’s tilt angle is used to determine the distance between the robot and the ball. The distance between robot-goalpost and the distance between robot-ball are processed with the difference of head servo’s pan angle and compass value using trigonometric formulas to determine the coordinates of the robot and the ball in the Cartesian coordinates

An Efficient Algorithm for Monitoring Practical TPTL Specifications

We provide a dynamic programming algorithm for the monitoring of a fragment of Timed Propositional Temporal Logic (TPTL) specifications. This fragment of TPTL, which is more expressive than Metric Temporal Logic, is characterized by independent time variables which enable the elicitation of complex real-time requirements. For this fragment, we provide an efficient polynomial time algorithm for off-line monitoring of finite traces. Finally, we provide experimental results on a prototype implementation of our tool in order to demonstrate the feasibility of using our tool in practical applications

Синтез моделей процессов по журналам событий с шумом

Process mining is a new emerging discipline related to process management, formal process models, and data mining. One of the main tasks of process mining is the model synthesis (discovery) based on event logs. A wide range of algorithms for process model discovery, analysis, and enhancement is developed. The real-life event logs often contain noise of different types. In this paper we describe the main causes of noise in the event logs and study the effect of noise on the performance of process discovery algorithms. The experimental results of application of the main process discovery algorithms to artificial event logs with noise are provided. Specially generated event logs with noise of different types were processed using the four basic discovery techniques. Although modern algorithms can cope with some types of noise, in most cases, their use does not lead to obtaining a satisfactory result. Thus, there is a need for more sophisticated algorithms to deal with noise of different types.Извлечение процессов (process mining) – новая и активно развивающаяся область исследований, тесно связанная с управлением процессами, формальными моделями процессов и извлечением данных (data mining). Одна из основных задач извлечения процессов – синтез (извлечение) модели процесса на основании анализа журнала событий. Разработан широкий спектр алгоритмов для извлечения, анализа и усовершенствования моделей процессов. Журналы событий реальных систем часто содержат шум различных видов. В данной работе описываются основные причины возникновения шума в журналах событий и изучается влияние шума на эффективность применения основных алгоритмов извлечения процессов. Приводятся экспериментальные результаты применения основных алгоритмов извлечения моделей процессов к искусственным журналам событий с шумами различного типа. Для этого специальным образом сгенерированные журналы событий с шумом обрабатывались с использованием четырех основных методов извлечения процессов. Хотя современные алгоритмы могут справляться с некоторыми типами шума, в большинстве случаев их применение не приводит к получению удовлетворительного результата. Таким образом, существует необходимость в разработке более совершенных подходов для журналов событий с шумом

From Formal Requirement Analysis to Testing and Monitoring of Cyber-Physical Systems

abstract: Cyber-Physical Systems (CPS) are being used in many safety-critical applications. Due to the important role in virtually every aspect of human life, it is crucial to make sure that a CPS works properly before its deployment. However, formal verification of CPS is a computationally hard problem. Therefore, lightweight verification methods such as testing and monitoring of the CPS are considered in the industry. The formal representation of the CPS requirements is a challenging task. In addition, checking the system outputs with respect to requirements is a computationally complex problem. In this dissertation, these problems for the verification of CPS are addressed. The first method provides a formal requirement analysis framework which can find logical issues in the requirements and help engineers to correct the requirements. Also, a method is provided to detect tests which vacuously satisfy the requirement because of the requirement structure. This method is used to improve the test generation framework for CPS. Finally, two runtime verification algorithms are developed for off-line/on-line monitoring with respect to real-time requirements. These monitoring algorithms are computationally efficient, and they can be used in practical applications for monitoring CPS with low runtime overhead.Dissertation/ThesisDoctoral Dissertation Computer Science 201