1,720,963 research outputs found
Introducing ontology best practices and design patterns into robotics: USAREnv
No full textSystems with knowledge representation and reasoning functionality are quite common within the robotics community. Nevertheless, most of the proposed architectures are ad-hoc implementations, which lack of modularity, standardization, and that cannot be reused or shared among different users. We fill that the Semantic Web effort over the past years in promoting standard representations and ontology best practices should be adopted by the robotic community, to foster the design of more effective and reusable systems, adapt for non expert users in everyday activities. In this paper, we investigate how to integrate ontology best practices and standard representations into the robotic system design, modelling an ontology for a real application field: urban search and rescue robotics. We also discuss the benefits of this methodology for robotic systems, as well as presenting some effective design guidelines. © 2010 The authors and IOS Press. All rights reserved
Evaluating tangible paradigms for ground robot teleoperation
No full textTangible user interfaces (TUIs) exhibit innovative interaction paradigms, for example through motion sensing, tactile feedback, or gesturing. Whilst wide spread in human-computer interaction, their value in robotic systems has still to be assessed. In this paper, we present some results obtained through an extensive experimental evaluation of motion sensing interaction paradigms implemented on TUIs for the teleoperation of ground robots. Once analyzed the collected data, in order to evince relevant properties of TUIs, we provide a detailed discussion of our results in terms of mission-related performance, environment conditions, robot operation degree, and human cognitive effort. Our belief is that such a study represents a valuable step towards a formal assessment of tangible interfaces in robotics. © 2011 IEEE
Tangible interfaces for robot teleoperation
No full textIn this paper we present some results obtained through an experimental evaluation of tangible user interfaces (TUIs), comparing their novel interaction paradigms with more conventional interfaces, such as a joypad and a keyboard. Our main goal is to make a formal assessment of TUIs in robotics through a rigorous and extensive experimental evaluation. Firstly, we identified the main benefits of TUIs for robot teleoperation in a urban search and rescue task. Secondly, we provide an evaluation framework to allow for an effective comparison of tangible interfaces with other input devices
The advantage of mobility: Mobile tele-operation for mobile robots
No full textIntra-scenario operator mobility is claimed to be a strong advantage when acquiring situational awareness within a robot tele-operation. This factor should not be discounted when seeking to build more effective Human-Robot Interaction (HRI) systems. In this paper, on the basis of extensive experimentation comparing a desktop-based interface wrt. a PDA-based interface for remote control of mobile robots, we provide support (and also some confutation) of this claim. The experiments were performed in order to identify the most suitable operator interface for controlling a mobile robot depending on the task and mobility/visibility of the operator
Knowledge acquisition through human-robot multimodal interaction
No full textThe limited understanding of the surrounding environment still restricts the capabilities of robotic systems in real world applications. Specifically, the acquisition of knowledge about the environment typically relies only on perception, which requires intensive ad hoc training and is not sufficiently reliable in a general setting. In this paper, we aim at integrating new acquisition devices, such as tangible user interfaces, speech technologies and vision-based systems, with established AI methodologies, to present a novel and effective knowledge acquisition approach. A natural interaction paradigm is presented, where humans move within the environment with the robot and easily acquire information by selecting relevant spots, objects, or other relevant landmarks. The synergy between novel interaction technologies and semantic knowledge leverages humans' cognitive skills to support robots in acquiring and grounding knowledge about the environment; such richer representation can be exploited in the realization of robot autonomous skills for task accomplishment. © 2012 Springer-Verlag Berlin Heidelberg
Technical Achievement Award in RoboCup Rescue Simulation League
No full textIl premio è stato conseguito per l e caratteristiche innovative dell'interfaccia del sistem
Improving Search and Rescue Using Contextual Information
No full textSearch and rescue (SAR) is a challenging application for autonomous robotics research. The requirements of this kind of application are very demanding and are still far from being met. One of the most compelling requirements is the capability of robots to adapt their functionalities to harsh and heterogeneous environments. In order to meet this requirement, it is common to embed contextual knowledge into robotic modules. We have previously developed a context-based architecture that decouples contextual knowledge, and its use, from typical robotic functionalities. In this paper, we show how it is possible to use this approach to enhance the performance of a robotic system involved in SAR missions. In particular, we provide a case study on exploration and victim detection tasks, specifically tailored to a given SAR mission. Moreover, we extend our contextual knowledge formalism in order to manage complex rules that deal with spatial and temporal aspects that are needed to model mission requirements. The approach has been validated through several experiments that show the effectiveness of the presented methodology for SAR. (C) Koninklijke Brill NV, Leiden and The Robotics Society of Japan, 200
- …
