Sistem ve Kontrol Mühendisliği Anabilim Dalı

Çevresel algılama ve harıtalama ıle ınsan takıbı

This thesis is concerned with human following by a mobile robot that also needs to navigate in a socially compliant manner. The importance of this problem is due to the increasing usage of service robots in human-populated areas. This is a challenging task because the robot needs to consider proxemics while navigating. At the same time, it needs to keep the human in sight. In this thesis, this problem is studied from four aspects. First, an extensive evaluation of the previously proposed social navigation method, Social APF-RL, has been conducted to verify that the robot's navigation is socially compliant. Following, in order to better keep the human target within its field of view, a social robot head design has been realized based on a pan-tilt mechanism. Thirdly, human following in a socially compliant manner has been considered using the developed robot head, including body-head coordination while navigating. For this, a deep learning network based on reinforcement learning has been developed. Finally, recovery in case of human target loss is considered through human tracking and environmental sensing of doors using a specially trained YOLOv8 network. All the proposed methods are tested extensively in the Gazebo simulation environment.

Giyilebilir sensörler ile kas yükü tahmini

Assessment of workload intensity and muscle load measurement is important to understand the quality of the intended motion. There have been numerous attempts to quantify workload levels for different motion for different parts of the body using wearable sensors. This thesis investigates human locomotion, particularly walking and running, which are fundamental activities of daily life. Electromyography (EMG) is a technique to quantify the level of muscle activity. In this study, the aim is to lay foundation for feature engineering and to build a machine learning model to predict EMG sensor output with minimal number of sensors during walking. Two pressure insole sensors and a single EMG - IMU combined sensor have been used during the experiments. The process starts with building a machine learning model to predict EMG sensor output using only raw input signals, which provided a poor accuracy. In order to improve the model, lagged features, derivatives and window-based statistics like moving averages and standard deviations are added to feature set and accuracy is improved. Then the focus is put on hyperparameter tuning and regularization is introduced to decrease overfitting. Although these steps led to incremental improvements, the test performance eventually plateaued with overfitting. In order to overcome this issue, data is shuffled before splitting it into training and test sets. After shuffling during training and test data split, the model delivered its best results—both training and test accuracy improved, and overfitting was significantly reduced.

A data mining approach to predict failures in banking sector

A survey on systems architecture development and a helicopter communication system conceptual design

A system is commonly defined to be a collection of hardware, software, people, and procedures organized to accomplish some common objectives. These objectives are required by the stakeholders of the system. Systems are not developed at a point in time. The system development process to bring a system into being and into operational use from user requirements, requires a systems development life cycle approach that includes analysis, design, implementation, integration, maintenance and retirement. To obtain efficient systems, in the design process of the system, system?s architecture is built to manage to prevent design conflicts and undesired solutions. System?s architecting contributes to the development of a system from its initial concept until its retirement from use in this life cycle process.This thesis mainly focuses on system?s architecture design context and systems architecture design methodologies. In the first chapter of the study, system development life cycle models and system?s architecting design process is introduced. In addition, the context of the systems architecure is explained. In the next chapter, Structured Architecture Methodology and Object Oriented Architecture Methodology are introduced and explained. In the last chapter the study is concluded by architecting a communication system of an attack helicopter by Structured Systems Architecture Methodology.Key Terms: Systems Architecture Context, Systems Architecture Methodologies, Structured Architecture Methodology, Object-Oriented Architecture Methodology

A surveillance algorithm for fall detection and initiation of an e-mail

Demographic patterns are demonstrating that the world is a maturing society. Advances in medical treatments extend people's life spans. Elderly care is a burden on families' and states' budget. Moreover, elder people want to age in their place without the breach of their privacy and losing independency. Statistically unexpected falls happen to one third of individuals in excess of 65. This thesis focuses on fall problem on elderly, who age at their place. Smart assisting for elderly is an essential need for health care and emergency response when needed. Since sleep assistance is a complex subject, this project covers only the part that, if they fall while standing or sitting they would get help. Thus this thesis aims to help people age in their place by providing fall detection via image processing. The approach can be described as data analysis and programming an algorithm in the area of fall detection. The system analyzes minimum bounding rectangle of a moving object, considers aspect ratio, centroid and diagonal angle. In the literature fall algorithms use computationally expensive algorithms to distinguish the focused person in the image. In this study distinguishing an inactive person is not included considering that a fall necessarily contains motion. The person of interest is distinguished with image differencing. However this technique amplifies the noise in the binarized image. This issue is eliminated using Gaussian filtering on differenced image. Due to experiment constraints an adequate amount of statistics was not possible to collect. However human movements can be imitated with computer software literally. For academic purposes open access to this software can make statistics available for fall algorithms. A series of scenarios of fall is presented in section 2.7.4 and for each category a sample was recorded. Scenarios are a total of 20 with 4 recoveries and 5 fall-like cases. Among them only 11 are real fall cases and they are all detected as true positives besides one. The rest 9 cases are either with recovery or fall like cases and only one of them gives a false positive alarm. Hence the true positive percentage is 91 per cent while the false positive ratio is 11, 1 per cent.