Search results for "Robot"
showing 10 items of 1036 documents
To defer or not to defer? A German longitudinal multicentric assessment of clinical practice in urology during the COVID-19 pandemic
2020
PLOS ONE 15(9), e0239027 (2020). doi:10.1371/journal.pone.0239027
Environment-Aware RSSI Based Positioning Algorithm for Random Angle Interference Cancellation in Visible Light Positioning System
2021
International audience; Visible Light Positioning (VLP) is considered to be one of the most promising candidates for future Location Based Service (LBSs). The traditional Received Signal Strength Indication (RSSI) based VLP system is highly sensitized with receiver's orientation. However, the assumption of the receiver's orientation fixed or perfectly known is not realistic in practice. Thus, a random angle between receiver and the horizontal plane inevitably appears among localization, which extremely affects positioning results. This paper proposed an Environment-Aware RSSI based positioning algorithm for VLP system. It enables to mainly eliminate random angle interference without the hel…
Visual Control of a Robotic Hand
2004
The paper deals with the design and implementation of a visual control of a robotic system composed of a dexterous hand and stereo cameras. The aim of the proposed system is to reproduce the movements of a human hand in order to learn complex manipulation tasks. A novelty algorithm for a robust and fast fingertips localization and tracking is presented. Moreover, a simulator is integrated in the system to give useful feedbacks to the users during operations, and provide robust testing framework for real experiments (see video).
A Posture Sequence Learning System for an Anthropomorphic Robotic Hand
2003
The paper presents a cognitive architecture for posture learning of an anthropomorphic robotic hand. Our approach is aimed to allow the robotic system to perform complex perceptual operations, to interact with an human user and to integrate the perceptions by a cognitive representation of the scene and the observed actions. The anthropomorphic robotic hand imitates the gestures acquired by the vision system in order to learn meaningful movements, to build its knowledge by different conceptual spaces and to perform complex interaction with the human operator.
A social humanoid robot as a playfellow for vocabulary enhancement
2018
We introduce a system that exploits a Pepper humanoid robot acting as a playfellow in a word-play game. The robot can play a portmanteau game by directly interacting with children, and it exploits a conversation engine, a portmanteau creation engine, and a definition engine. The humanoid can play the role of either an answerer or a generator of new words.
Portmanteau Word-Play for Vocabulary Enhancement with Humanoid Robot Support
2018
Word-play is as powerful learning and motivation tool often used by educators for teaching the ability of reading, which is a complex activity. In this paper, we introduce a system that exploits a Pepper humanoid robot acting as a playfellow in a word-play game based on portmanteau words. The robot shows the ability to play with children using a conversation engine, a portmanteau creation engine, and a definition engine. In this manner, Pepper can integrate itself within a group of kids, and it can support a teacher in her activities. The humanoid can be involved in a word-based round-game in which it can play the role of either answerer or generator of new words.
Detection of Internet robots using a Bayesian approach
2015
A large part of Web traffic on e-commerce sites is generated not by human users but by Internet robots: search engine crawlers, shopping bots, hacking bots, etc. In practice, not all robots, especially the malicious ones, disclose their identities to a Web server and thus there is a need to develop methods for their detection and identification. This paper proposes the application of a Bayesian approach to robot detection based on characteristics of user sessions. The method is applied to the Web traffic from a real e-commerce site. Results show that the classification model based on the cluster analysis with the Ward's method and the weighted Euclidean metric is very effective in robot det…
Modeling a non-stationary bots’ arrival process at an e-commerce Web site
2017
Abstract The paper concerns the issue of modeling and generating a representative Web workload for Web server performance evaluation through simulation experiments. Web traffic analysis has been done from two decades, usually based on Web server log data. However, while the character of the overall Web traffic has been extensively studied and modeled, relatively few studies have been devoted to the analysis of Web traffic generated by Internet robots (Web bots). Moreover, the overwhelming majority of studies concern the traffic on non e-commerce websites. In this paper we address the problem of modeling a realistic arrival process of bots’ requests on an e-commerce Web server. Based on real…
Efficient on-the-fly Web bot detection
2021
Abstract A large fraction of traffic on present-day Web servers is generated by bots — intelligent agents able to traverse the Web and execute various advanced tasks. Since bots’ activity may raise concerns about server security and performance, many studies have investigated traffic features discriminating bots from human visitors and developed methods for automated traffic classification. Very few previous works, however, aim at identifying bots on-the-fly, trying to classify active sessions as early as possible. This paper proposes a novel method for binary classification of streams of Web server requests in order to label each active session as “bot” or “human”. A machine learning appro…
Time series clustering with different distance measures to tell Web bots and humans apart
2022
The paper deals with the problem of differentiating Web sessions of bots and human users by observing some characteristics of their traffic at the Web server input. We propose an approach to cluster bots’ and humans’ sessions represented as time series. First, sessions are expressed as sequences of HTTP requests coming to the server at specific timestamps; then, they are pre-preprocessed to form time series of limited length. Time series are clustered and the clustering performance is evaluated in terms of the ability to partition bots and humans into separate clusters. The proposed approach is applied to real server log data and validated with the use of different time series distance meas…