Gabriele Randelli

Speech technologies nowadays available on mobile devices show an increased performance both in terms of the language that they are able to capture and in terms of reliability. The availability of performant speech recognition engines suggests the deployment of vocal interfaces also in consumer robots. In this paper, we report on our current work, by specifically focussing on the difficulties that arise in grounding the user’s utterances in the environment where the robot is operating.

The 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… Visualizza altro

The 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. Meno dettagli

Tangible 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… Visualizza altro

Tangible 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. Meno dettagli

Mobile robots can accomplish high-risk tasks without exposing humans to danger: robots go where humans fear to tread. Until the time in which completely autonomous robots are fully deployed, remote operators will be required in order to fulfill desired missions. Remotely controlling a robot requires that the operator receives the information about the robot’s surroundings, as well as its location in the scenario. Based on a set of experiments conducted with users, we evaluate the performance of… Visualizza altro

Mobile robots can accomplish high-risk tasks without exposing humans to danger: robots go where humans fear to tread. Until the time in which completely autonomous robots are fully deployed, remote operators will be required in order to fulfill desired missions. Remotely controlling a robot requires that the operator receives the information about the robot’s surroundings, as well as its location in the scenario. Based on a set of experiments conducted with users, we evaluate the performance of operators when they are provided with a hand-held-based interface or a desktop-based interface. Results show how performance depends on the task asked of the operator and the scenario in which the robot is moving. The conclusions prove that the operator’s intra-scenario mobility when carrying a hand-held device can counterbalance the limitations of the device. By contrast, the experiments show that if the operator cannot move inside of the scenario, his performance is significantly better when using a desktop-based interface. These results set the basis for a transfer of control policy in missions involving a team of operators, some equipped with hand-held devices and others working remotely with desktop-based computers. Meno dettagli

In this paper we address the use of knowledge representation and reasoning (KR&R) techniques in current research and implementation of robotic systems. We quickly overview the work on knowledge representation and reasoning, since the area became popular in the eighties, starting from the assumption that entitles the paper: “Suppose you have a robot”. Then, we survey the relatively few recent approaches that try to improve the capabilities of robotic systems, by exploiting an explicit… Visualizza altro

In this paper we address the use of knowledge representation and reasoning (KR&R) techniques in current research and implementation of robotic systems. We quickly overview the work on knowledge representation and reasoning, since the area became popular in the eighties, starting from the assumption that entitles the paper: “Suppose you have a robot”. Then, we survey the relatively few recent approaches that try to improve the capabilities of robotic systems, by exploiting an explicit representation of knowledge. The availability of cheap and powerful robots makes it feasible to embody intelligence in physical agents, and the motivations for embedding KR&R components in robotic agents become more and more compelling. Unfortunately, there is still a gap in performance that knowledge representation and reasoning have not yet filled in. We argue that one possibility to improve this state of affairs is to build systems that, by exploiting several AI technologies, support human robot interaction to make robots more knowledgeable with the help of humans. Meno dettagli

In 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… Visualizza altro

In 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. Meno dettagli

Robotic systems are today capable of performing patrolling and surveillance tasks in indoor structured environments. However, they need to be designed by taking into account the operational environment and the specific task to be accomplished. This dependency from the specific features of task and environment (contextual information, according to Turner), severely restricts their practical deployment. In this paper, we address the creation of semantic maps for the effective deployment of… Visualizza altro

Robotic systems are today capable of performing patrolling and surveillance tasks in indoor structured environments. However, they need to be designed by taking into account the operational environment and the specific task to be accomplished. This dependency from the specific features of task and environment (contextual information, according to Turner), severely restricts their practical deployment. In this paper, we address the creation of semantic maps for the effective deployment of surveillance robot in an a priori unknown indoor scenario. More specifically, we propose an architecture based on multimodal human-robot interaction that allows the user to specify in a natural way, knowledge about the environment that is represented in a semantic map. Given the acquired knowledge, the robot is then capable to plan and execute an effective patrolling of the scenario. Meno dettagli

Systems 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… Visualizza altro

Systems 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. Meno dettagli

Emergency and exploration missions are accomplished by remote stationary personnel and on-site responders that can deploy robots for dealing with situations involving hazard or inaccessibility. Thus, human-robot interaction (HRI) plays a key role in these kinds of applications. Intra-scenario operator mobility is often considered to be advantageous for acquiring situational awareness (SA) in the context of robot teleoperation, but non portable devices can provide a greater volume of processed… Visualizza altro

Emergency and exploration missions are accomplished by remote stationary personnel and on-site responders that can deploy robots for dealing with situations involving hazard or inaccessibility. Thus, human-robot interaction (HRI) plays a key role in these kinds of applications. Intra-scenario operator mobility is often considered to be advantageous for acquiring situational awareness (SA) in the context of robot teleoperation, but non portable devices can provide a greater volume of processed information. This should not be discounted when trying to build more effective human-robot interaction (HRI) in search and rescue (SAR) or exploration missions. In this paper, we report a set of experiments comparing a desktop-based interface with a PDA-based interface for remote control of mobile robots. Our goal is two-fold. First we aim at defining which kinds of operators have the best SA under different conditions. Second, we investigate a control transfer policy for determining when an operator should hand over to another, depending on the device, the task and the context. Meno dettagli

Search 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… Visualizza altro

Search 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. Meno dettagli

Intra-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… Visualizza altro

Intra-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. Meno dettagli