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We study the problem of object recognition on robotic platforms where large image collections of target objects are unavailable and where new models of previously unseen objects must be added dynamically. This situation is common in robotics, where task related objects can require recognition over multiple viewpoints and training examples are sparse. The proposed framework uses pre-trained convolutional...
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...
The grant for the research gives the researcher the important opportunity to make fruitful research results. Recently, the notification of the government grants and some Foundation grants in the various fields informs the researchers through Internet. However, the notification provided through Internet includes ambiguous and complex. The researchers will fail to notice the grant information which...
In active orthoses for paraplegic users, it is essential that the devices replicate the user's leg movements. This is usually performed through joint position control, where each orthosis joint follows a specific angle trajectory as a reference. The most commonly used approach for generating this required references is to create a set of average joint trajectories from a gait database, and use them...
The human brain has self-organization capability after paralysis caused by stork. This needs neuro-rehabilitation for stroke-patients. Recently, robotic technology is successfully applied in the rehabilitation. Most of robot rehabilitation devices are in 2-dimension, and do not have feedback from the environment. The rehabilitation effectiveness is not so good. In this paper, we design a 3-demension...
In this document we present an intelligence device which includes a monitor system for automatic movements of a robotic hospital bed based on posture classification and identification. This functionality has been developed in response to the requirements defined by the application of a diagnostic methodology [10]. Our diagnostic methodology applied on a Mexican public hospital allowed us to understand...
Nowadays, the communication between human and machines have occurred, at most of the cases, throught text due to the fact the oral communication to involve two main aspects: the understanding of the spoken language and the recognition voice, that are unsolved research topics yet. However, it is notable the progress that the areas of voice recognition and synthetizer have gotten in the last decade...
We propose a discriminative compact scene descriptor for single-view cross-season place recognition. Unlike previous bag-of-words approaches which rely on a library of vector quantized visual features, the proposed scene descriptor is based on a library of raw image data (such as available visual experience, images shared by other colleague robots, and publicly available image data on the web) that...
We have studied the problem of retrieval of arbitrary object instances from a large point cloud data set. The context is autonomous robots operating for long periods of time, weeks up to months and regularly saving point cloud data. The ever growing collection of data is stored in a way that allows ranking candidate examples of any query object, given in the form of a single view point cloud, without...
Predicting the outcome of an action can help a robot detect failures in advance, and schedule action replanning before an error occurs. We propose using an interactive physics based simulator with the aim of collecting realistic data to be used for learning. We then show how we save and query for specific information from the data more effectively. The data from the simulation is used to learn a failure...
Thanks to a remarkably great ability to show amusement and engagement, laughter is one of the most important social markers in human interactions. Laughing together can actually help to set up a positive atmosphere and favors the creation of new relationships. This paper presents a data collection of social interaction dialogs involving humor between a human participant and a robot. In this work,...
In this work we address the problem of finding replacements of missing objects that are needed for the execution of human-like manipulation tasks. This is a usual problem that is easily solved by humans provided their natural knowledge to find object substitutions: using a knife as a screwdriver or a book as a cutting board. On the other hand, in robotic applications, objects required in the task...
Biometrics, an important research field emerging fast, has growing challenges related to the secured access and security of the systems protected. In this paper, the secured access to a smart robot is proposed using biometrics. The robot can be accessed by recognizing the user's face image, acting as a password, and also operates on the voice-commands given by the speaker. The face recognition technique...
In India like many other countries, the crimes especially against women are rising. One of the many reasons perhaps is the low conviction rate. The initial stage of criminal investigation starts with the exploration of evidences and eyewitnesses. An eyewitness can act as a guide to trace out the suspect. Her/his perception about the suspect can be useful to identify the criminal. Based on the descriptions...
A supervisor's delayed intervention on a student's performance deficiencies seriously affects a research progress. Due to the demanding schedules of supervisors, it is a challenge for them to timely observe the performance deficiencies of the student. To mitigate this situation, we propose an agent-based system to enhance, control and manage the research supervision process. Specifically, the system...
In this paper, we propose a modularized architecture for a robot arm object fetching system integrated with 3D CAD-model based object recognition system that can cope with objects in random types and poses. The interface and the core functionality of each module in the architecture are discussed in detail. Implementation of each module is also conducted. Furthermore, the assumptions and the working...
In this paper, we address the challenging problem of single-view cross-season place recognition. A new approach is proposed for compact discriminative scene descriptor that helps in coping with changes in appearance in the environment. We focus on a simple effective strategy that uses objects whose appearance remain the same across seasons as valid landmarks. Unlike popular bag-of-words (BoW) scene...
The main aim of this paper is an improvement of the famous Scale Invariant Feature Transform (SIFT) algorithm used in place categorization. Masking approach to reduce the computational complexity of SIFT have been proposed. Tradeoff between key points and processing time on feature extraction has been used. Selected parameters used in the experiment demonstrated that the computational cost of SIFT...
To provide the elderly with appropriate and timely caregiving in activities of daily life (ADL), it is desired for robots to have the capability of intention awareness (IA). Different from existing context-specific intention awareness (CSIA) approaches which are based on a limited and passive knowledge database, our approach, named ‘WebIA’, adopts a novel web query approach to establish a vast and...
In this paper, we introduce a dictionary learning framework using RGB-D covariance descriptors on point cloud data for performing object classification. Dictionary learning in combination with RGB-D covariance descriptors provides a compact and flexible description of point cloud data. Furthermore, the proposed framework is ideal for updating and sharing dictionaries among robots in a decentralized...
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