Visually-guided walking reference modification for humanoid robots

Humanoid robots are expected to assist humans in the future. As for any robot with mobile characteristics, autonomy is an invaluable feature for a humanoid interacting with its environment. Autonomy, along with components from artificial intelligence, requires information from sensors. Vision sensors are widely accepted as the source of richest information about the surroundings of a robot. Visual information can be exploited in tasks ranging from object recognition, localization and manipulation to scene interpretation, gesture identification and self-localization. Any autonomous action of a humanoid, trying to accomplish a high-level goal, requires the robot to move between arbitrary waypoints and inevitably relies on its selflocalization abilities. Due to the disturbances accumulating over the path, it can only be achieved by gathering feedback information from the environment. This thesis proposes a path planning and correction method for bipedal walkers based on visual odometry. A stereo camera pair is used to find distinguishable 3D scene points and track them over time, in order to estimate the 6 degrees-of-freedom position and orientation of the robot. The algorithm is developed and assessed on a benchmarking stereo video sequence taken from a wheeled robot, and then tested via experiments with the humanoid robot SURALP (Sabanci University Robotic ReseArch Laboratory Platform)

Trajectory Tracking Control of a Four Rotor Unmanned Aerial Vehicle Based on Continuous Sliding Mode Controller

In this paper, a nonlinear Continuous Sliding Mode control (CSMC) application is presented for trajectory tracking control of a four rotor unmanned aerial vehicle (UAV) called the Quadrotor, also known as micro helicopter. The proposed controller is tested with different time-varying reference routes to provide a stable flight for position control. To show the effectiveness of the designed CSMC, well-tuned PI controller is also applied to quadrotor for the same routes. The current position of the quadrotor is taken from accelerometer, gyroscope and ultrasonic sensors. The experimental results show that the CSMC is adequate to dealing with parameter uncertainties occur in the system dynamics while flying and has satisfactory performance in terms of robustness against to disturbances and error elimination when it compared with PI controller

A new deep convolutional neural network model for classifying breast cancer histopathological images and the hyperparameter optimisation of the proposed model

Deep learning algorithms have yielded remarkable results in medical diagnosis and image analysis, besides their contribution to improvements in a number of fields such as drug discovery, time-series modelling and optimisation methods. With regard to the analysis of histopathologic breast cancer images, the similarity of those images and the presence of healthy and tumourous tissues in different areas complicate the detection and classification of tumours on whole slide images. An accurate diagnosis in a short time is a need for full treatment in breast cancer. A successful classification on breast cancer histopathological images will overcome the burden on the pathologist and reduce the subjectivity of diagnosis. In this study, we propose a deep convolutional neural network model. The model uses various algorithms (i.e., stochastic gradient descent, Nesterov accelerated gradient, adaptive gradient, RMSprop, AdaDelta and Adam) to compute the initial weight of the network and update the model parameters for faster backpropagation learning. In order to train the model with less hardware in a short time, we used the parallel computing architecture with Cuda-enabled graphics processing unit. The results indicate that the deep convolutional neural network model is an effective classification model with a high performance up to 99.05% accuracy value. © 2020, Springer Science+Business Media, LLC, part of Springer Nature

ALET (Automated Labeling of Equipment and Tools): A Dataset, a Baseline and a Usecase for Tool Detection in the Wild

Robots collaborating with humans in realistic environments will need to be able to detect the tools that can be used and manipulated. However, there is no available dataset or study that addresses this challenge in real settings. In this paper, we fill this gap by providing an extensive dataset (METU-ALET) for detecting farming, gardening, office, stonemasonry, vehicle, woodworking and workshop tools. The scenes correspond to sophisticated environments with or without humans using the tools. The scenes we consider introduce several challenges for object detection, including the small scale of the tools, their articulated nature, occlusion, inter-class invariance, etc. Moreover, we train and compare several state of the art deep object detectors (including Faster R-CNN, Cascade R-CNN, RepPoint and RetinaNet) on our dataset. We observe that the detectors have difficulty in detecting especially small-scale tools or tools that are visually similar to parts of other tools. This in turn supports the importance of our dataset and paper. With the dataset, the code and the trained models, our work provides a basis for further research into tools and their use in robotics applications.Comment: 7 pages, 4 figure

Clinical value of pre-operative polyvinyl alcohol embolization in juvenile nasopharyngeal angiofibroma

Jüvenil nazofarengeal anjiofibromun tedavisinde pre-operatif embolizasyonun yeri tartışmalıdır. Embolizasyonun klinik etkinliğini değerlendirmek amacıyla, kliniğimizde 1994-2000 yılları arasında histopatolojik tanısı Jüvenil nazofarengeal anjiofibrom gelen, embolizasyon uygulanan ve uygulanmayan on hasta retrospektif olarak analiz edilmiştir. Bu vakaların beşine polivinil alkol ile selektif embolizasyon uygulanmıştır. Sadece cerrahi tedavi uygulanan olgulardaki intra-operatif kanama miktarı ortalama 2530 cc, verilen transfüzyon ünitesi ortalama 4.4 unit olarak bulunmuştur. Cerrahi öncesi pre-operatif embolizasyon uygulanan olgularda ise intra-operatif kanama miktarı ortalama 1590 cc, verilen transfüzyon ünitesi ise ortalama 2 unittir. Sonuçlar, pre-operatif polivinil alkol ile embolizasyonun intra-operatif kanama miktarını, transfüzyon ihtiyacını ve operasyon süresini azaltmada güvenilir ve etkili bir yöntem olduğunu göstermiştir.Role of the pre-operative embolization in the treatment of Juvenile nasopharyngeal angiofibroma, is controversial. For the purpose of evaluating clinical effectiveness of embolization, ten patients who came to our clinic with histopathological diagnosis of Juvenile nasopharyngeal angiofibroma and who are and not administered embolization between 1994 and 2000, have been retrospectively analyzed. in five of the cases, selective embolization method has been administered with polyvinyl alcohol (PVA). in cases where only surgical treatment is administered, it is found that average intraoperative bleeding amount is 2530 cc and transfusion unit administered is 4.4 units, in the cases where preoperative embolization is administered, intraoperative bleeding amount is 1590 cc and number of transfusion units is 2. Results indicated that embolization with preoperative polyvinyl alcohol is a reliable and effective method in decreasing the amount of intraoperative bleeding, transfusion need and duration of the surgical operation

Dört bacaklı robotlar için önizlemeli kontrol ile sıfır moment noktası tabanlı yürüme yörüngesi sentezi

Bacakları üzerinde hareket eden robotların engel aşma konusunda önemli avantajları söz konusudur. Özellikle dört bacaklı robotların değişken arazi yapıları üzerinde birçok uygulamaları düşünülmektedir. Bu çalışmada, dört bacaklı bir robotun düz zemin üzerinde hızlı yol almasına yönelik tırıs türü ilerleme üzerinde durulmaktadır. Sıfır Moment Noktası (SMN) karalılık kriterine ve Doğrusal Ters Sarkaç Modeli’ne (DTSM) dayalı bir yürüme referansı sentez yöntemi sunulmaktadır. Tırıs ilerleme için bir SMN referans yörüngesi önerilmiş, bu yörüngeden, önizlemeli kontrol yaklaşımı ile Robot Ağırlık Merkezi (RAM) için bir referans yörünge elde edilmiştir. Oluşturulan ağırlık merkezi yörüngesi ters kinematik yöntemi ile bacak eklemlerinin konum referanslarının hesaplanmasında kullanılmıştır. Önerilen referans sentezi yöntemi, 16 serbestlik dereceli bir robot modeli ile üç boyutlu ve tam dinamikli bir simülasyon ortamında denenmiştir. Simülasyon sonuçları sunulan yaklaşımın başarılı olduğunu göstermektedir

Dört bacaklı robotlar için önizleme kontrolü ve sıfır moment noktası esaslı yürüyüş yörüngesi üretimi

Robota verilen görevde engel aşımı gerektiğinde bacaklı robotların geri kalan mobil robotlara göre önemli avantajları bulunmaktadır. Bu makalede dört bacaklı robotların düz bir yüzeyde yürüyüşü için bir ölçümleme üretimi yöntemi sunuldu. Bu yaklaşım sıfır moment noktası (SMN) temelli kararlılık ve doğrusal ters sarkaç modeli (DTSM) üzerinedir. Yürüyüş için SMN referans gezingeleri ileri sürülüp oradan önizleme kontorü vasıtasıyla robotun ağırlık merkezi (RAM) referansı için referans gezingeleri elde edildi. Bacak eklemlerinin pozisyonları RAM referans gezingeleri üzerine ters kinematik uygulanarak hesaplandı. Öne sürülen referans gezinge üretimi sentezi, tamamen dinamik 3 boyutlu benzetimle test edildi. Benzetimde 16 serbestlik derecesine (SD) sahip dört bacaklı robot modeli kullanıldı. Benzetim sonuçları, yürüyüş için yapılan referans üretim tekniğinin başarıya ulaştığını gösteriyor

Repositioning of the global epicentre of non-optimal cholesterol

High blood cholesterol is typically considered a feature of wealthy western countries(1,2). However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world(3) and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health(4,5). However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe