Human-Robot Motion: An Attention-Based Navigation Approach

International audienceMobile robot companions are service robots that are mobile and designed to share our living space. For such robots, mobility is essential and their coexistence with humans adds new aspects to the mobility issue: the first one is to obtain appropriate motion and the second one is interaction through motion. We encapsulate these two aspects in the term Human-Robot Motion (HRM) with reference to Human-Robot Interaction. The long-term issue is to design robot companions whose motions, while remaining safe, are deemed appropriate from a human point of view. This is the key to the acceptance of such systems in our daily lives. The primary purpose of this paper is to explore how the psychological concept of attention can be taken into account in HRM. To that end, we build upon an existing model of attention that computes an attention matrix that describes how the attention of each person is distributed among the different elements, persons and objects, of his/her environment. Using the attention matrix, we propose the novel concept of attention field that can be viewed as an attention predictor. Using different case studies, we show how the attention matrix and the attention field can be used in HRM

Human-Robot Motion: Taking Attention into Account

Mobile robot companions are service robots that are mobile and designed to share our living space. For such robots, mobility is essential and their coexistence with humans adds new aspects to the mobility issue: the first one is to obtain appropriate motion and the second one is interaction through motion. We encapsulate these two aspects in the term Human-Robot Motion (HRM) with reference to Human-Robot Interaction. The long-term issue is to design robot companions whose motions, while remaining safe, are deemed appropriate from a human point of view. This is the key to the acceptance of such systems in our daily lives. The purpose of this paper is to explore how the psychological concept of attention can be taken into account in HRM. To that end, we build upon an existing model of attention that computes an attention matrix that describes how the attention of each person is distributed among the different elements, persons and objects, of the environment. Using the attention matrix, we propose the novel concept of attention field that can be viewed as an attention predictor. Using different case studies, we show how the attention matrix and the attention field can be used in HRM.Les robots compagnons mobiles sont des robots de service conçus pour partager et se déplacer dans notre espace de vie. Pour de tels robots, la mobilité est essentielle et leur coexistence avec des humains ajoute de nouveaux aspects à ce sujet de recherche: le premier est d'obtenir un mouvement approprié et le second est l'interaction au travers du mouvement. On regroupe ces deux aspects sous le terme Human-Robot Motion (HRM) en référence à Human-Robot Interaction. L'objectif à long terme est la conception de robots compagnons dont le mouvement, tout en restant sans danger, est jugé approprié d'un point de vue humain. Ceci est la clé de l'acceptation de tels systèmes dans notre vie quotidienne. L'objectif de ce papier est d'explorer comment le concept psychologique d'attention peut être prix en compte dans HRM. A cette fin, nous proposons un concept nouveau de champ attentionnel qui peut être vu comme un prédicteur attentionnel. Nos travaux se basent sur un modèle existant qui quantifie l'attention humaine et fournit une matrice attentionnelle qui décrit la distribution des ressources attentionnelles de chaque personne entre les différents éléments, personnes et objets de son environnement. Le calcul du champ attentionnel introduit découle de cette matrice attentionnelle. En considérant différents scénarios d'étude, on montre comment la matrice et le champ attentionnel(le) peuvent être utilisés en HRM

JPEG Steganography and Synchronization of DCT Coefficients for a Given Development Pipeline

This short paper proposes to use the statistical analysis of the correlation between DCT coefficients to design a new synchronization strategy that can be used for cost-based steganographic schemes in the JPEG domain. First, an analysis is performed on the covariance matrix of DCT coefficients of neighboring blocks after a development similar to the one used to generate BossBase. This analysis exhibits groups of uncorrelated coefficients: 4 groups per block and 2 groups of uncorrelated diagonal neighbors together with groups of mutually correlated coefficients groups of 6 coefficients per blocs and 8 coefficients between 2 adjacent blocks. Using the uncorrelated groups, an embedding scheme can be designed using only 8 disjoint lattices. The cost map for each lattice is updated firstly by using an implicit underlying Gaussian distribution with a variance directly computed from the embedding costs, and secondly by deriving conditional distributions from multivariate distributions. The covariance matrix of these distributions takes into account both the correlations exhibited by the analysis of the covariance matrix and the variance derived from the cost. This synchronization scheme enables to obtain a gain of PE of 5% at QF 95 for an embedding rate close to 0.3 bnzac coefficient using DCTR feature sets

Secundaire preventie na een residentiële ontwenningsbehandeling voor jongeren

Verslaving is een complexe ziekte met een chronisch verloop en opeenvolgende crisissituaties die een acute aanpak vereisen. Het residentieel programma is een eerste stap in de behandeling. Hier wordt de basis gelegd voor een nieuw, clean leven. In de laatste fase van het residentieel programma ligt de nadruk op resocialisatie: de uitbouw van een nieuwe vriendenkring, zinvolle daginvulling, werk, hobby’s en huisvesting. Eens deze basis er is, wordt de patiënt ‘losgelaten’ en moet hij het waarmaken in het ‘echte’ leven. Hij moet de veiligheid en geborgenheid van de kliniek missen en hij is de eerste maanden na zijn ontslag uiterst kwetsbaar. Het is dan ook belangrijk dat de patiënt in die kwetsbare periode intensief kan opgevolgd worden. Tot nog toe werd de patiënt verwezen naar een ambulante setting met ongekende therapeuten, met wie hij geen binding heeft. De patiënt ziet dit meestal niet zitten en haakt vroegtijdig af, met vaak een herval als gevolg. Om deze ‘missing link’ tussen residentiële behandeling en een stabiel leven op te vullen, werd ons intensief nazorgprogramma ontwikkeld. Het nazorgproject legt de nadruk op een actieve participatie van hulpverlener, patiënt en zijn omgeving en een intensieve wisselwerking tussen de verschillende actoren. Er is een continuïteit van hulpverlening die de zaken verder kan opvolgen en direct kan interveniëren bij crisissituaties. Op deze manier kan vaak een herval vermeden worden of de schade beperkt gehouden

Human-Robot Motion: Taking Attention into Account

Mobile robot companions are service robots that are mobile and designed to share our living space. For such robots, mobility is essential and their coexistence with humans adds new aspects to the mobility issue: the first one is to obtain appropriate motion and the second one is interaction through motion. We encapsulate these two aspects in the term Human-Robot Motion (HRM) with reference to Human-Robot Interaction. The long-term issue is to design robot companions whose motions, while remaining safe, are deemed appropriate from a human point of view. This is the key to the acceptance of such systems in our daily lives. The purpose of this paper is to explore how the psychological concept of attention can be taken into account in HRM. To that end, we build upon an existing model of attention that computes an attention matrix that describes how the attention of each person is distributed among the different elements, persons and objects, of the environment. Using the attention matrix, we propose the novel concept of attention field that can be viewed as an attention predictor. Using different case studies, we show how the attention matrix and the attention field can be used in HRM.Les robots compagnons mobiles sont des robots de service conçus pour partager et se déplacer dans notre espace de vie. Pour de tels robots, la mobilité est essentielle et leur coexistence avec des humains ajoute de nouveaux aspects à ce sujet de recherche: le premier est d'obtenir un mouvement approprié et le second est l'interaction au travers du mouvement. On regroupe ces deux aspects sous le terme Human-Robot Motion (HRM) en référence à Human-Robot Interaction. L'objectif à long terme est la conception de robots compagnons dont le mouvement, tout en restant sans danger, est jugé approprié d'un point de vue humain. Ceci est la clé de l'acceptation de tels systèmes dans notre vie quotidienne. L'objectif de ce papier est d'explorer comment le concept psychologique d'attention peut être prix en compte dans HRM. A cette fin, nous proposons un concept nouveau de champ attentionnel qui peut être vu comme un prédicteur attentionnel. Nos travaux se basent sur un modèle existant qui quantifie l'attention humaine et fournit une matrice attentionnelle qui décrit la distribution des ressources attentionnelles de chaque personne entre les différents éléments, personnes et objets de son environnement. Le calcul du champ attentionnel introduit découle de cette matrice attentionnelle. En considérant différents scénarios d'étude, on montre comment la matrice et le champ attentionnel(le) peuvent être utilisés en HRM

Human-Robot Motion: Taking Human Attention into Account

International audienceLet Human-Robot Motion (HRM) denote the study of how robots should move among people, the work presented herein explores to what extent human attention can be useful to address HRM. To that end, a computational model of the human visual attention is proposed, it determines how a person's attentional resources are distributed among the items in her/his environment. Based on this model, the concept of attention field for a robot is developed and then used to define different attentional properties for the robot's motions such as distraction or surprise. Said attentional properties are finally exploited to design an acceptable motion planner capable of computing motions that are non-distracting and non-surprising, but also paths that convey the robot's intention to interact with a person

Human-Robot Motion: An Attention-Based Navigation Approach

International audienceMobile robot companions are service robots that are mobile and designed to share our living space. For such robots, mobility is essential and their coexistence with humans adds new aspects to the mobility issue: the first one is to obtain appropriate motion and the second one is interaction through motion. We encapsulate these two aspects in the term Human-Robot Motion (HRM) with reference to Human-Robot Interaction. The long-term issue is to design robot companions whose motions, while remaining safe, are deemed appropriate from a human point of view. This is the key to the acceptance of such systems in our daily lives. The primary purpose of this paper is to explore how the psychological concept of attention can be taken into account in HRM. To that end, we build upon an existing model of attention that computes an attention matrix that describes how the attention of each person is distributed among the different elements, persons and objects, of his/her environment. Using the attention matrix, we propose the novel concept of attention field that can be viewed as an attention predictor. Using different case studies, we show how the attention matrix and the attention field can be used in HRM