An Autonomous Mobile Robotic System for Surveillance of Indoor Environments

The development of intelligent surveillance systems is an active research area. In this context, mobile and multi-functional robots are generally adopted as means to reduce the environment structuring and the number of devices needed to cover a given area. Nevertheless, the number of different sensors mounted on the robot, and the number of complex tasks related to exploration, monitoring, and surveillance make the design of the overall system extremely challenging. In this paper, we present our autonomous mobile robot for surveillance of indoor environments. We propose a system able to handle autonomously general-purpose tasks and complex surveillance issues simultaneously. It is shown that the proposed robotic surveillance scheme successfully addresses a number of basic problems related to environment mapping, localization and autonomous navigation, as well as surveillance tasks, like scene processing to detect abandoned or removed objects and people detection and following. The feasibility of the approach is demonstrated through experimental tests using a multisensor platform equipped with a monocular camera, a laser scanner, and an RFID device. Real world applications of the proposed system include surveillance of wide areas (e.g. airports and museums) and buildings, and monitoring of safety equipment

A.: Optimization of the POSIT algorithm for indoor autonomous navigation

Abstract This paper presents an optimization of POSIT (Pose from Orthographic and Scaling with Iterations), a model-based camera location algorithm, in the domain of indoor mobile robot navigation. The method finds the rotation matrix and the translation vector of the camera with respect to an object. The novelty of the proposed modified algorithm is that it does not need the perfect knowledge of camera parameters. A new definition of the scaling factor has been introduced in the scaled orthographic projection. Due to the peculiarity of the indoor bounded workspace a new formulation of the translation vector has been used. The new method has been successfully applied in a real environment considering a goal-directed navigation task for our real robot Khepera. The experimentation has shown better results in comparison with the original POSIT algorithm

αρογη ´- A System for the Virtual Aided Recomposition of Fragmented Frescos

Abstract. The paper describes a digital system for the virtual aided recomposition of fragmented frescos, an innovative approach that is being developed and proved on the St. Matthew’s fresco, painted by Cimabue in the Upper Church of St. Francis in Assisi which had an extension of 35 squared meters and broke into more than 140.000 pieces during the earthquake in 1997. The base level of the designed system transposes the traditional recomposition process in a digital way: the laboratory of fragments in Assisi, used for the traditional recomposition, becomes a client-server architecture that can be geographically distributed. Several operators can jointly work on the same fresco from different clients connected over Internet to a server, situated in our Institute in Bari, where a database has been designed and realized to contain the digital image of each single fragment. Several further features have been added to improve the efficiency and efficacy of the recomposition process. The database is indexed using a query-by-example approach applied to suitable sample images (fragments and/or details extracted from the reference image of the whole fresco). Colour and texture has been used as features to describe the pictorial content of fragments. Since the only available picture of the whole fresco has been acquired in unknown conditions and exhibits colours significantly different from those of fragments, it has been necessary to estimate and apply suitable and specific colour transformations to different regions of the reference image to make meaningful their comparison. The restorers of the Central Institute for Restoration, which cooperates in this project, are very interested in this strongly innovative approach. They are working on the St. Matthew’s fresco using the system and have pointed out several advantages that the system brings into their work as long as many new features that can enrich its possibilities. 1

Self positioning to observe prehistoric paints in a cave

Abstract. The enjoyment and survey of archaeological caves, hardly accessible by human beings, can be executed with the aid of a mobile vehicle. In this context, a fundamental task for the autonomous robot navigation is the selfpositioning with respect to a predefined target. The need of a non invasive intervention in the cave requires the use of natural landmarks as reference points. In this context, we have applied the modified POSIT algorithm (camera pose estimation method) by using a photograph of the prehistoric wall paintings of the archeological cave “Grotta dei Cervi”. First, feature extraction technique has been carried out, then, the position of the robot has been computed. The results obtained by using the experimental test bed in our laboratory are very encouraging for the experimentation in the real environment.