Suitable task allocation in intelligent systems for assistive environments

The growing need of technological assistance to provide support to people with special needs demands for systems more and more efficient and with better performances. With this aim, this work tries to advance in a multirobot platform that allows the coordinated control of different agents and other elements in the environment to achieve an autonomous behavior based on the user’s needs or will. Therefore, this environment is structured according to the potentiality of each agent and elements of this environment and of the dynamic context, to generate the adequate actuation plans and the coordination of their execution.Peer ReviewedPostprint (author's final draft

Anticipating human activities from object interaction cues

A real time approach to the recognition of human activity based on the interaction with objects in domestic settings is presented. It is based on capturing partial images where the activity takes place using a color camera, and processing the images to recognize the present objects and their location changes. For object description and recognition, a histogram on a normalized chromaticity space has been selected. The interaction with the objects is classified as four types of possible actions regarding change in location (add, remove, move or unchanged). Activities are defined as receipts, where objects plays the role of ingredients, tools or substitutes. Sensed objects and actions are then used to analyze in real time the probability of the human activity that is being performed at the moment in a continuous activity sequence. Tests are carried on a automated kitchen scenario where proactive assistance wants to be implemented taking into account the early recognition user activity.Peer Reviewe

Anticipating human activities from object interaction cues

A real time approach to the recognition of human activity based on the interaction with objects in domestic settings is presented. It is based on capturing partial images where the activity takes place using a color camera, and processing the images to recognize the present objects and their location changes. For object description and recognition, a histogram on a normalized chromaticity space has been selected. The interaction with the objects is classified as four types of possible actions regarding change in location (add, remove, move or unchanged). Activities are defined as receipts, where objects plays the role of ingredients, tools or substitutes. Sensed objects and actions are then used to analyze in real time the probability of the human activity that is being performed at the moment in a continuous activity sequence. Tests are carried on a automated kitchen scenario where proactive assistance wants to be implemented taking into account the early recognition user activity.Peer Reviewe