Robots and Cultural Heritage: New Museum Experiences

The introduction of new technologies to enhance the visiting museum experience is not a novelty. A large variety of interactive systems are nowadays available, including virtual tours, which makes cultural heritage accessible remotely. The theme of increase in accessibility and attractiveness has lately been faced with the employment of the service robotics, covering various types of applications. Regrettably, many of robotics solutions appear less successful in terms of utility and usability. On the basis of this awareness, a design for a new robotic solution for cultural heritage has been proposed. The project, developed at the royal residence of Racconigi Castle, consists of a telepresence robot designed as a tool to explore inaccessible areas of the heritage. The employed robot, called Virgil, was expressly designed for the project. The control of the robot is entrusted to the museum guides in order to enhance their work and enrich the cultural storytelling

Virgil, Robot for Museum Experience: Study on the opportunity given by robot capability to integrate the actual museum visit

Robotics platforms are becoming more and more present in people everyday life. A reflection on multimedia technologies that are currently used in the museum experiences has been made. In this paper, we present and describe a robotic system, called "Virgil" and a remote tele-operation application used as a support instrument for the museum guide in order to enhance the museum experience and increase the cultural value of the territorial heritage. The application is based on a Cloud Robotic infrastructure that contains ROS nodes and exposes a set of APIs to the user

An application of Kullback-Leibler divergence to active SLAM and exploration with particle filters

Autonomous exploration under uncertain robot position requires the robot to plan a suitable motion policy in order to visit unknown areas while minimizing the uncertainty on its pose. The corresponding problem, namely active SLAM (Simultaneous Localization and Mapping) and exploration has received a large attention from the robotic community for its relevance in mobile robotics applications. In this work we tackle the problem of active SLAM and exploration with Rao-Blackwellized Particle Filters. We propose an application of Kullback-Leibler divergence for the purpose of evaluating the particle-based SLAM posterior approximation. This metric is then applied in the definition of the expected gain from a policy, which allows the robot to autonomously decide between exploration and place revisiting actions (i.e., loop closing). The technique is shown to enhance robot awareness in detecting loop closing occasions, which are often missed when using other state-of-the-art approaches. Results of extensive tests are reported to support our claims

Rao-Blackwellized Particle Filters Multi Robot SLAM with Unknown Initial Correspondences and Limited Communication

Multi robot systems are envisioned to play an important role in many robotic applications. A main prerequisite for a team deployed in a wide unknown area is the capability of autonomously navigate, exploiting the information acquired through the on-line estimation of both robot poses and surrounding environment model, according to Simultaneous Localization And Mapping (SLAM) framework. As team coordination is improved, distributed techniques for filtering are required in order to enhance autonomous exploration and large scale SLAM increasing both efficiency and robustness of operation. Although Rao-Blackwellized Particle Filters (RBPF) have been demonstrated to be an effective solution to the problem of single robot SLAM, few extensions to teams of robots exist, and these approaches are characterized by strict assumptions on both communication bandwidth and prior knowledge on relative poses of the teammates. In the present paper we address the problem of multi robot SLAM in the case of limited communication and unknown relative initial poses. Starting from the well established single robot RBPF-SLAM, we propose a simple technique which jointly estimates SLAM posterior of the robots by fusing the prioceptive and the eteroceptive information acquired by each teammate. The approach intrinsically reduces the amount of data to be exchanged among the robots, while taking into account the uncertainty in relative pose measurements. Moreover it can be naturally extended to different communication technologies (bluetooth, RFId, wifi, etc.) regardless their sensing range. The proposed approach is validated through experimental tes

Leveraging the Cloud for Connected Service Robotics Applications

Cloud robotics is a new approach to robotics that exploits the internet as a resource for parallel computing and data sharing. Robots are no more considered as isolated devices but now they can add new functionalities, communicate with the environment and share knowledge base. Exploiting this new technology a robot can also take advantages by off-loading heavy computations to the cloud, thus reducing hardware costs, power consumption. The Joint Open Lab on Connected Robotic Applications laB (JOL CRAB) is a research laboratory created by Telecom Italia in collaboration with Politecnico di Torino. The aim is to investigate technologies and develop concepts where the focus is mainly placed on the relationship between robots and the cloud computing, addressing issues that arise from the use of robotic services in public/enterprise environments not only of technological, legal, economical, sociological or psychological kind, but also related to ergonomics, cognitive perception, and relational experience. The collaboration between university and the industry led to different field trials where issues and feasibility of new services were evaluated and a community of stakeholders was created in the territory. We present these field trials, the different issues that arise and how that can be solved

A cloud robotics system for telepresence enabling mobility impaired people to enjoy the whole museum experience

We present a novel robotic telepresence platform composed by a semi-autonomous mobile robot based on a cloud robotics framework, which has been developed with the aim of enabling mobility impaired people to enjoy museums and archaeological sites that would be otherwise inaccessible. Such places, in fact, very often are not equipped to provide access for mobility impaired people, in particular because these aids require dedicated infrastructures that may not fit within the environment and large investments. For this reason, people affected by mobility impairments are often unable to enjoy a part or even the entire museum experience. Solutions allowing mobility impaired people to enjoy museum experience are often based on recorded tours, thus they do not allow active participation of the user. On the contrary, the presented platform is intended to allow users to enjoy completely the museum round. A robot equipped with a camera is placed within the museum and users can control it in order to follow predefined tours or freely explore the museum. Our solution ensures that users see exactly what the robot is seing in real-time. The cloud robotics platform controls both navigation capabilities and teleoperation. Navigation tasks are intended to let the robot reliably follow pre-defined tours, while main concern of teleoperation tasks is to ensure robot safety (e.g., by means of dynamic obstacle detection and avoidance software). Proposed platform has been optimized to maximize user experience