1,721,021 research outputs found
Personality- and Memory-Based Software Framework for Human-Robot Interaction
No full textThe synergic orchestration of the cognitive and psychological dimensions characterizes human intelligence. Accordingly, carefully designing this mechanism in artificial intelligence can be a successful strategy to increase human likeness in a robot, enhancing mutual understanding and building a more natural and intuitive interaction. For this purpose, the main contribution of this work is a psychological and cognitive architecture tailored for HRI based on the interplay between robotic personality and memory-based cognitive processes. Indeed, the artificial personality manifests itself not only in various aspects of the behavior but also within the action selection process, which is closely intertwined with personality-dependent hedonic experiences linked to memories. Within this paper, we propose a task- and platform-independent framework, evaluated in a multiparty collaborative scenario. Obtained results show that a robot connected to our proposed framework is perceived as a cognitive agent capable of manifesting perceivable and distinguishable personality traits
Usability evaluation with different viewpoints of a Human-Swarm interface for UAVs control in formation
No full textA common way to organize a high number of robots, both when moving autonomously and when controlled by a human operator, is to let them move in formation. This is a principle that takes inspiration from the nature, that maximizes the possibility of monitoring the environment and therefore of anticipating risks and finding targets. In robotics, alongside these reasons, the organization of a robot team in a formation allows a human operator to deal with a high number of agents in a simpler way, moving the swarm as a single entity. In this context, the typology of visual feedback is fundamental for a correct situational awareness, but in common practice having an optimal camera configuration is not always possible. Usually human operators use cameras on board the multirotors, with an egocentric point of view, while it is known that in mobile robotics overall awareness and pattern recognition are optimized by exocentric views. In this article we present an analysis of the performance achieved by human operators controlling a swarm of UAVs in formation, accomplishing different tasks and using different point of views. The control architecture is implemented in a ROS framework and interfaced with a 3D simulation environment. Experimental tests show a degradation of performance while using egocentric cameras with respect of an exocentric point of view, although cameras on board the robots allow to satisfactorily accomplish simple tasks
Knowledge-Grounded Dialogue Flow Management for Social Robots and Conversational Agents
No full textThe article proposes a system for knowledge-based conversation designed for Social Robots and other conversational agents. The proposed system relies on an Ontology for the description of all concepts that may be relevant conversation topics, as well as their mutual relationships. The article focuses on the algorithm for Dialogue Management that selects the most appropriate conversation topic depending on the user input. Moreover, it discusses strategies to ensure a conversation flow that captures, as more coherently as possible, the user intention to drive the conversation in specific directions while avoiding purely reactive responses to what the user says. To measure the quality of the conversation, the article reports the tests performed with 100 recruited participants, comparing five conversational agents: (i) an agent addressing dialogue flow management based only on the detection of keywords in the speech, (ii) an agent based both on the detection of keywords and the Content Classification feature of Google Cloud Natural Language, (iii) an agent that picks conversation topics randomly, (iv) a human pretending to be a chatbot, and (v) one of the most famous chatbots worldwide: Replika. The subjective perception of the participants is measured both with the SASSI (Subjective Assessment of Speech System Interfaces) tool, as well as with a custom survey for measuring the subjective perception of coherence
Robot-Induced Group Conversation Dynamics: A Model to Balance Participation and Unify Communities
No full textThe purpose of this research is to study the impact of robot participation in group conversations and assess the effectiveness of different addressing policies. The study involved a total of 300 participants, who were divided into groups of four and engaged in a dialogue with a humanoid robot. The robot acted as a moderator, using information obtained during the conversation to determine which speaker to address. The study found that the policy used by the robot significantly impacted the conversation dynamics. Specifically, the robot provided more balanced attention to each participant and reduced the number of subgroups
Cloud Services for Social Robots and Artificial Agents
No full textThis work presents the design and the implementation of CAIR: a cloud system for knowledge-based interaction devised for Social Robots and other conversational agents. The system is structured in a way that it can be easily expanded by adding new services that improve the capabilities of the clients connected to the Cloud. Another key feature of the system is that it has been designed to make the development of its clients straightforward: in this way, multiple devices (e.g., robots, computers, smartphones, etc.) can be easily endowed with the capability of autonomously interacting with the user, understanding when to perform specific actions, and exploiting all the information provided by services on the Cloud
A GAN-based Approach for Generating Culture-Aware Co-Speech Gestures
No full textEmbedding social robots with the capability of accompanying their sentences with natural gestures may be the key to increasing their acceptability and their usage in real contexts. However, it could be argued that the definition of natural communicative gestures is not trivial, since it strictly depends on the culture of the person interacting with the robot. The proposed work investigates the usage of Generative Adversarial Networks (GANs) for generating culture-dependent communicative gestures based on speech audio features. To this aim, a custom dataset, only composed of persons belonging to the same culture, has been created, to extract all keypoints and audio features needed to train the network. Then, a generative model, also consisting of a voice conversion module, has been implemented and tested with the humanoid robot Pepper. Preliminary results, obtained through objective measurements and subjective evaluation, show that the proposed approach may be promising for generating culture-dependent communicative gestures for social robots
Ethical concerns in rescue robotics: a scoping review
No full textRescue operations taking place in disaster settings can be fraught with ethical challenges. Further ethical challenges will likely be introduced by the use of robots, which are expected to soon become commonplace in search and rescue missions and disaster recovery efforts. To help focus timely reflection on the ethical considerations associated with the deployment of rescue robots, we have conducted a scoping review exploring the relevant academic literature following a widely recognized scoping review framework. Of the 429 papers identified by the first screening, six fulfilled the selection criteria of our literature review. Quantitative data synthesis showed that a subset of the papers includes a qualitative experimental exploration of the ethical issues at hand, with workshops involving both experts and potential users. Most use simulations or scenarios to anticipate the ethical implications and other consequences of using robots in search and rescue missions. Qualitative text analysis identified seven core ethically relevant themes: fairness and discrimination; false or excessive expectations; labor replacement; privacy; responsibility; safety; trust. Our results suggest that the literature on ethics in rescue robotics is scant and disparate, but the papers identified uniformly endorsed a proactive approach to handling the ethical concerns associated with the use of robots in disaster scenarios
Strategies for Controlling the Conversation Dynamics in Multi-Party Human-Robot Interaction
No full textThis article tackles the research question of whether it is possible to control conversation dynamics in a multi-party scenario using easily implementable solutions on off-the-shelf robotic platforms. To this end, we expanded upon our previously developed cloud robotic architecture by incorporating policies aimed at managing conversation dynamics through selective addressing of individuals, with the ultimate goal of balancing or unbalancing users’ participation or making subgroups of participants interact. Specifically, we computed the dominance of each speaker as a weighted sum of their speaking time and the number of words spoken within a moving window and used the Louvain algorithm to partition speakers into a set of non-overlapping communities. We then implemented six control policies, which were applied by the robot. Two of them, named BH and BS, aim to reduce dominance error (i.e., the difference in dominance between the most and least dominant speakers—both policies give the floor to the less dominant speaker). Two other policies, UH and US, are designed to increase the dominance error (both give the floor to the most dominant speaker). Finally, CH and CS aim to reduce the community error (i.e., the difference between the actual number of detected subgroups among speakers and the ideal target of a single group to which all speakers belong). Policies BH, UH, and CH (with “H” standing for “hard”) do not allow any exceptions to the policy rules, while BS, US, and CS (with “S” for “soft”) permit exceptions. To test the impact of these policies, we conducted a between-subjects study (N = 300) involving middle school students engaging in dialogue with a humanoid robot acting as a moderator. The study compared five conditions: in four of them, the robot used information gathered during the conversation to decide which speaker to address, applying one of the control policies—BH, BS, CH, or CS. The policies UH and US were excluded, as having a robot consistently give the floor to the most dominant child may raise ethical concerns. In the fifth condition, a baseline neutral policy (N) was applied, in which the robot did not explicitly address any speaker. The results imply that a robot using the proper control policies can influence conversation dynamics to keep both dominance error and community error significantly lower than those of a robot using the baseline policy, leading to more balanced participation and a reduction in the number of subgroups. Indeed, statistically significant differences have been found between the five policies considered in the dominance and community errors. However, no statistically significant differences in user experience—as measured by three scales of the validated SASSI questionnaire—were found when the robot used one of the control policies, as compared to the baseline, suggesting that participants are not negatively impacted by the robot’s attempt to control the conversation
Multiparty Verbal Interaction between Humans and Artificial Agents
No full textThe study of verbal interaction between multiple humans and robots is an almost unexplored research field. This kind of interaction has been primarily analyzed in the literature focusing on cooperation to achieve a common task or on more technical aspects such as active speaker recognition. The presented work proposes a holistic approach to solve the problem: a cloud architecture that allows social robots and artificial agents to interact verbally with a group of people. The system can recognize the active speaker and decide who to address based on the developed policies while also correctly keeping track of the conversation state
Visual feedback with multiple cameras in a UAVs Human-Swarm Interface
No full textIn all situations in which a wide area has to be monitored, a practice emerging in recent years consists in using Unmanned Aerial Vehicles (UAVs), and in particular multirotors. Even if many steps forward have been taken toward the fully autonomous control of UAVs, a human pilot is usually in charge of controlling the robots. However, teleoperating UAVs can become a hard task whenever it is necessary to deploy a swarm of robots instead of a single unit, to the end of increasing the area under observation. In this case, the organization of robots in a structured formation may reduce the effort of the operator to control the swarm. When controlling a team of robots, the typology of visual feedback is crucial. It is known that, while overall awareness and pattern recognition are optimized by exocentric views, i.e., with cameras from above the swarm, the immediate environment is often better viewed egocentrically, i.e., with cameras on board the robots. In this article we present the implementation of a human-robot interface for the control of a swarm of UAVs, with a focus on the analysis of the effects of different visual feedbacks on the performance of human operators
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