In this paper, we address the problem of fusing information about object positions in multirobot systems. Our approach is novel in two main respects. First, it addresses the multirobot object localization problem using fuzzy logic. It uses fuzzy sets to represent uncertain position information and fuzzy intersection to fuse this information. The result of this fusion is a consensus among sources, as opposed to the compromise achieved by many other approaches. Second, our method fully propagates self-localization uncertainty to object-position estimates. We evaluate our method using systematic experiments, which describe an input-error landscape for the performance of our approach. This landscape characterizes how well our method performs when faced with various types and amounts of input errors.

Highly heterogeneous robotic systems are becoming increasingly common, as are robotic systems integrated with smart environments. In such distributed systems, there are many different sources and types of information, which need to be coordinated and combined effectively. The problem of cooperative anchoring is (roughly) the problem of, in a distributed system, determining which items of information refer to the same objects, and combining these items accordingly. In this paper, we define a general computational framework for cooperative anchoring inspired by work on conceptual spaces and (single-robot) perceptual anchoring. We also discuss an implementation of this framework which uses tools from fuzzy logic, and we present an illustrative experiment.

The vision of an ecology of physically embedded intelligent systems, or PEIS-Ecology, combines insights from the fields of autonomous robotics and ambient intelligence to provide a new approach to building robotic systems in the service of people. In this paper, we present this vision, and we report the results of a four-year collaborative research project between Sweden and Korea aimed at the concrete realization of this vision.We focus in particular on three results: a robotic middleware able to cope with highly heterogeneous systems; a technique for autonomous self-configuration and reconfiguration; and a study of the problem of sharing information of both physical and digital nature.

Perceptual anchoring is the process of linking action to the appropriate objects in the environment via perception. The pivot of anchoring is the inclusion of micromodels of the world, or anchors, into a controller. In this paper, we propose to use anchors to focus the perceptual effort according to the current needs of the controller. We describe an active gaze control strategy able to maintain anchoring of several objects in a dynamic environment, and show how we have used it in a team of legged robots in the RoboCup'99 international robot soccer competition.