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This paper addresses the problem of anomaly detection on rotating machinery in industrial environments using single channel audio signals. The proposed algorithm is based on image processing feature analysis obtained from the image representation of the Short-time Fourier Transform of reference and degraded audio signals. In order to assess the potential of the algorithm, a 8 signals database is recorded...
This paper focuses on the real time control of autonomous robot through the detection of multiple types of motor imagery. The EEG data contains when subject performs imagery motor activity. The motor imagery activity includes movements of left hand, right hand, left leg and right leg. For feature extraction, the cross-correlation method is used to calculate six statistical features (mean, median,...
The introduction of social robots in human living spaces has brought to attention the need for robots to be equipped with emotion recognition capabilities to facilitate natural and social human-robot interactions. This paper explores the recognition of continuous dimensional emotion from facial expressions. It further investigates the use of principal component analysis (PCA), locality preserving...
Post-construction quality assessment is an integrated part of any construction project which plays a vital role for the entire project. Existing repetitive, labor intensive and less productive manual inspection methods make the construction quality assessment automation a necessary research topic. In contrast to the manual inspection methods, recent advances in robotic technologies and low cost sensors...
An autonomous mobile robot, working with human teammates, should be equipped to intelligently react to changes in team behavior without relying on directives from human team members. To respond appropriately to changes in team behavior, the robot should detect when these situations occur, and correctly classify the new team behavior. We demonstrate a method for detecting and classifying behavior changes...
In the context of autonomous navigation, vision has demonstrated its potential in replacing bulkier sensors and achieving multi-tasking, operating as the primary sensor for guidance as well as simultaneously fulfilling other dedicated missions. Vision sensors are of particular interest in aerial navigation where their versatility and light weight simplify the avionics and increase the available payload...
Indonesian Robotic Competition is an annual robot competition conducted by Indonesian minister of education. One of branch competition is robot dance whereas robot should dance according to Indonesian traditional music. The aim of this study is to make an application that is capable to recognize instrument especially gong in javanesse traditional music so that it can helps future development of robot...
In this paper, we present a method to classify the category of clothing item. When visually recognizing clothing items based on their shapes, two types of shape variations make the recognition difficult: physical deformation and the variety of size and design. In order to lessen the effect of deformation, first, the item of interest is reshaped into one of a small number of limited shapes. To absorb...
The study of emotions has attracted considerable attention in several areas, from artificial intelligence and psychology to neuroscience. The use of emotions in decisionmaking processes is an example of how multi-disciplinary they are. To be able to communicate better with humans, robots should use appropriate communicational gestures, considering the emotions of their human conversation partners...
Noise robust speech recognition is crucial for effective human-machine interaction in real-world environments. Sound source separation (SSS) is one of the most widely used approaches for addressing noise robust speech recognition by extracting a target speaker's speech signal while suppressing simultaneous unintended signals. However, conventional SSS algorithms, such as independent component analysis...
Place recognition has been intensively studied in the context of robot vision. BoW-based approach gains its popularity for its efficiency and robustness using features extracted from images. Many features have been examined in the past for place recognition purpose. However, there is no such feature that can outperform others in all environments. Each feature has its own advantage, thus, they should...
Derived from ecological psychology, the term ‘affordance’ refers to the functional classification of objects. It simply means the set of actions a subject (i.e. humans and anthropomorphic agents) can possibly perform with an object. There are several paradigms in the researches regarding the approaches of affordance detection. These approaches include considering other contexts like the subject, ambient...
Human action recognition plays a vital role in the field of human-robot interaction and is widely researched for its potential applications. In this paper we propose a human action recognition framework for human robot interaction in industrial applications. First, a set of key descriptors are learned from a collection of weak spatio-temporal skeletal joint descriptors using random forests, which...
Vast variety of EMG signal applications have been proposed and practiced on EMG control system such as rehabilitation and prosthetic hand and so on. In this paper, a realization of a robust real time robotic arm control system is proposed. First, the root mean square (RMS) of EMG signal for a hand movement is measured and the measured EMG signal is transformed to a complex number. Secondly, the transformed...
Today most recognition pipelines are trained at an off-line stage, providing systems with pre-segmented images and predefined objects, or at an on-line stage, which requires a human supervisor to tediously control the learning. Self-Supervised on-line training of recognition pipelines without human intervention is a highly desirable goal, as it allows systems to learn unknown, environment specific...
We introduce a novel active stereo vison-based object tracking system for a humanoid robot. The system tracks a moving object that is dynamically changing its appearance and scale. The system features an in-built learning process that simultaneously learns short term models for the object and potential distractors. These models evolve over time, rectifying the inaccuracies of the tracking in a cluttered...
Non-intrusive person recognition in different poses is a crucial task in the field of human-robot interaction (HRI). Most of the previous work for person recognition were based on face. In these approaches, if the person's face is invisible to the robot, it will ask the person to stand in a location suitable for the robot and look at the robot to recognize him. However in a normal interaction, the...
Intrusion detection systems designed for conventional computer systems and networks are not necessarily suitable for mobile cyber-physical systems, such as robots, drones and automobiles. They tend to be geared towards attacks of different nature and do not take into account mobility, energy consumption and other physical aspects that are vital to a mobile cyber-physical system. We have developed...
This study presents fault detection of a heavy duty V94.2 gas turbine which has 162.1 MW nominal power and 50 Hz nominal frequency and is located at Pareh Sar power plant, Gilan, Iran. For this purpose stored data include measurements of relative and absolute vibration of shaft bearings in both turbine and compressor sections. Signal processing techniques and mathematical transformations are used...
In this paper, we research the real-time object tracking technology. The object tracking algorithm discussed in this paper is developed based on the Tracking-Learning-Detection(TLD) and the Centroid Neural Network(CNN). The object is unknown ahead of tracking, the model of the object is composed of objects transformed geometrically immediately after tracking. The TLD framework is useful for long-term...
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