Internal conflict, in which a character is torn by opposing motivations, is central to drama. Actors portray such conflict in part by mimicking involuntary behaviors that occur as a result of such conflicts. In this paper, we examine the role of timing – pauses and hesitation, in particular – in internal conflict. We argue that virtual actors can be made more expressive if we can emulate the underlying structures of inhibition and conflict detection believed to operate in the human system. We discuss work in progress on this problem that uses the Twig procedural animation system.

An important issue in time series classification problems is to find representative prototypes. Especially for roughly segmented time series with spatial distortions, such as human gestures, it is complicated to find templates, which optimally represent signal classes. In this paper we present an approach to find optimal time series prototypes in subseries of class templates. Our optimization approach is based on separability measures for prototype candidates and utilizes (but is not limited to) DTW in order to tackle the problem of spatial and temporal distortions. The search for prototypes in the target space is performed by means of a brute force search as well as an evolution strategy. In our experiments with an artificial dataset we show that brute force search optimization is able to improve the time series classification result and that the application of an evolution strategy yields comparable target function scores while reducing computing time.

This paper gives a short overview of time representations in current symbol grounding architectures. Furthermore we report on a recently developed embodied language acquisition system that acquires object words from a linguistically unconstrained human-robot dialogue. Conceptual issues in future development of the system towards the acquisition of action words will be discussed briefly.

The present privacy legislation continue to be drafted on the basis of the Strasburg Convention of 1981. The mere fact that present privacy laws are based on principles drafted 29 years ago, when the web did not exist, shows that privacy legislation need to make a quantum leap to be in line with the realities of to-day’s real life operating environment. If the status quo is kept, the law and its application shall face serious (and sometimes insurmountable) obstacles to its implementation, making compliance costly for private business, at the same time jeopardizing effectiveness of privacy protection for individuals. A new set of rules should be drafted and established, addressing the changed environment of information and communication technology, in order to allow free flow of information at the same time assuring due protection of personal data.

While there is a plethora of mechanisms to ensure lawful access to privacy-protected data, additional research is required in order to reassure individuals that their personal data is being used for the purpose that they consented to. This is particularly important in the context of new data mining approaches, as used, for instance, in biomedical research and commercial data mining. We argue for the use of computational workflows to ensure and enforce appropriate use of sensitive personal data. Computational workflows describe in a declarative manner the data processing steps and the expected results of complex data analysis processes such as data mining (Gil et al. 2007b; Taylor et al. 2006). We see workflows as an artifact that captures, among other things, how data is being used and for what purpose. Existing frameworks for computational workflows need to be extended to incorporate privacy policies that can govern the use of data.

Lane changing on highways is stressful. In this paper, we present RASCL, the Robotic Assistance System for Changing Lanes. RASCL combines state-of-the-art sensing and localization techniques with an accurate map describing road structure to detect and track other cars, determine whether or not a lane change to either side is safe, and communicate these safety statuses to the user using a variety of audio and visual interfaces. The user can interact with the system through specifying the size of their “comfort zone”, engaging the turn signal, or by simply driving across lane dividers. Additionally, RASCL provides speed change recommendations that are predicted to turn an unsafe lane change situation into a safe situation and enables communication with other vehicles by automatically controlling the turn signal when the driver attempts to change lanes without using the turn signal.

Roboticists need to have a solid understanding of hardware and software. The standard computer science education in the United States, however, tends to teach students only about software. To remedy this situation, we explore new ways of teaching them about hardware in a playful way. Realizing that pinball machines are simple robots, we have developed a pinball machine interface between a PC and a recent Lord of the Rings pinball machine, which enables students to implement pinball games and gain knowledge of hardware and interface programming in the process. This paper describes both our pinball machine interface and our experience developing it. As far as we know, this is the first time that anyone has managed to control an existing pinball machine completely.

In this paper we show how the shape of a 2D-landmark configuration can be encoded based on qualitative 1D-ordering information and how relevant geometric shape properties of a landmark configuration (strictly based on ordering information) can be detected by a sequence of view-based snapshots. Furthermore we show how shape of landmark configurations supports view-based localization tasks specially in the face of erroneous and missing sensor information.

In 3 experiments, participants learned bone anatomy by using a hand-held controller to rotate an on-screen 3D bone model. The on-screen bone included (OR condition) or did not include (no-OR condition) orientation references—visible lines marking its axes. The learning task involved rotating the on-screen bone to match target orientations. Learning outcomes were assessed by having participants identify anatomical features from different orientations. On the learning task, the OR group performed more accurately, directly, and quickly than the control group and high-spatial individuals outperformed low-spatial individuals. Assessments of anatomy learning indicated that under more challenging conditions, ORs elevated learning by low-spatial individuals to near that of high-spatial individuals. In Experiment 3, orientation references were shown to help learners avoid disorientation due to the symmetrical shape of the object.

Medical experts routinely need to identify the shapes of anatomical structures, and surgeons report that they depend substantially on touch to help them with this process. In this paper, we discuss possible reasons why touch may be especially important for anatomical shape recognition in surgery, and why in this domain haptic cues may be at least as informative about shape as visual cues. We go on to discuss modern surgical methods, in which these haptic cues are substantially diminished. We conclude that a potential future challenge is to find ways to reinstate these important cues and to help surgeons recognize shapes in the restricted sensory conditions of minimally invasive surgery.