Leveraging sponsorships on the Internet: Activation, congruence, and articulation

This paper considers how the Internet can be used to leverage commercial sponsorships to enhance audience attitudes toward the sponsor. Definitions are offered that distinguish the terms leverage and activation with respect to sponsorship-linked marketing; leveraging encompasses all marketing communications collateral to the sponsorship investment, whereas activation relates to those communications that encourage interaction with the sponsor. Although activation in many instances may be limited to the immediate event-based audience, leveraging sponsorships via sponsors' Web sites enables activation at the mass-media audience level. Results of a Web site navigation experiment demonstrate that activational sponsor Web sites promote more favorable attitudes than do nonactivational Web sites. It is also shown that sponsorsponsee congruence effects generalize to the online environment, and that the effects of sponsorship articulation on audience attitudes are moderated by the commerciality of the explanation for the sponsor-sponsee relationship. Importantly, the study reveals that attitudinal effects associated with variations in leveraging, congruence, and orientation of articulation may be sustained across time.

Mapping of indoor environments by robots using low-cost vision sensors

For robots to operate in human environments they must be able to make their own maps because it is unrealistic to expect a user to enter a map into the robot’s memory; existing floorplans are often incorrect; and human environments tend to change. Traditionally robots have used sonar, infra-red or laser range finders to perform the mapping task. Digital cameras have become very cheap in recent years and they have opened up new possibilities as a sensor for robot perception. Any robot that must interact with humans can reasonably be expected to have a camera for tasks such as face recognition, so it makes sense to also use the camera for navigation. Cameras have advantages over other sensors such as colour information (not available with any other sensor), better immunity to noise (compared to sonar), and not being restricted to operating in a plane (like laser range finders). However, there are disadvantages too, with the principal one being the effect of perspective. This research investigated ways to use a single colour camera as a range sensor to guide an autonomous robot and allow it to build a map of its environment, a process referred to as Simultaneous Localization and Mapping (SLAM). An experimental system was built using a robot controlled via a wireless network connection. Using the on-board camera as the only sensor, the robot successfully explored and mapped indoor office environments. The quality of the resulting maps is comparable to those that have been reported in the literature for sonar or infra-red sensors. Although the maps are not as accurate as ones created with a laser range finder, the solution using a camera is significantly cheaper and is more appropriate for toys and early domestic robots.

Topological SLAM Using Fast Vision Techniques

In this paper we propose a method for vision only topological simultaneous localisation and mapping (SLAM). Our approach does not use motion or odometric information but a sequence of colour histograms from visited places. In particular, we address the perceptual aliasing problem which occurs using external observations only in topological navigation. We propose a Bayesian inference method to incrementally build a topological map by inferring spatial relations from the sequence of observations while simultaneously estimating the robot's location. The algorithm aims to build a small map which is consistent with local adjacency information extracted from the sequence measurements. Local adjacency information is incorporated to disambiguate places which otherwise would appear to be the same. Experiments in an indoor environment show that the proposed technique is capable of dealing with perceptual aliasing using visual observations only and successfully performs topological SLAM.

Topological SLAM using neighbourhood information of places

Perceptual aliasing makes topological navigation a difficult task. In this paper we present a general approach for topological SLAM~(simultaneous localisation and mapping) which does not require motion or odometry information but only a sequence of noisy measurements from visited places. We propose a particle filtering technique for topological SLAM which relies on a method for disambiguating places which appear indistinguishable using neighbourhood information extracted from the sequence of observations. The algorithm aims to induce a small topological map which is consistent with the observations and simultaneously estimate the location of the robot. The proposed approach is evaluated using a data set of sonar measurements from an indoor environment which contains several similar places. It is demonstrated that our approach is capable of dealing with severe ambiguities and, and that it infers a small map in terms of vertices which is consistent with the sequence of observations.

Designing interaction for local communications : an urban screen study

This paper discusses the ongoing design and use of a digital community noticeboard situated in a suburban hub. The design intention is to engage residents, collect and display local information and communications, and spark discussion. A key contribution is an understanding of Situated Display navigation that aids retrieval from a long-term collection created by and for suburban community, and engaging qualities of this collection.