Lars-Erik Janlert

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Recognizing activities based on an actor’s object manipulation is an important research approach within ubiquitous computing. We present an approach which complements object manipulation with an actor’s situational information by viewing the everyday objects used by the actor to perform his/her activities from an “egocentric perspective”. Two concepts,(More)
This is the final report from a pre-study on Emergent Interaction. The purpose of the pre-study was to get a clearer idea of what emergent interaction is, what it can be used for, and what the problems are, as a preparation for a larger study. The project is an Umeå Center for Interaction Technology (UCIT) and Ericsson Erisoft collaboration, with(More)
In this paper we present an approach for high-level behavior recognition and selection integrated with a low-level controller to help the robot to learn new skills from demonstrations. By means of Semantic Network as the core of the method, the robot gains the ability to model the world with concepts and relate them to low-level sensory-motor states. We(More)
The visions of ambient intelligence demand novel interaction paradigms that enable designers and system developers to frame and manage the dynamic and complex interaction between humans and environments populated with physical (real) and virtual (digital) objects of interest. So far, many proposed approaches have adhered to a devicecentric stance when(More)
This paper describes our efforts in modeling and tracking a human agent’s situation based on their possibilities to perceive and act upon objects (both physical and virtual) within smart environments. A Situative Space Model is proposed. WLAN signal-strength-based situative space tracking system that positions objects within individual situative(More)
Two methods for behavior recognition are presented and evaluated. Both methods are based on the dynamic temporal difference algorithm Predictive Sequence Learning (PSL) which has previously been proposed as a learning algorithm for robot control. One strength of the proposed recognition methods is that the model PSL builds to recognize behaviors is(More)
Designers of mobile context-aware systems are struggling with the problem of conceptually incorporating the real world into the system design. We present a body-centric modeling framework (as opposed to device-centric) that incorporates physical and virtual objects of interest on the basis of proximity and human perception, framed in the context of an(More)