Search results for "Human-Robot Interaction"
showing 10 items of 37 documents
Vision and emotional flow in a cognitive architecture for human-machine interaction
2011
The detection and recognition of a human face should meet the need for social interaction that drives a humanoid robot, and it should be consistent with its cognitive model and the perceived scene. The paper deals with the description of the potential of having a system of emotional contagion, and proposes a simple implementation of it. An emotional index allows to build a mechanism which tends to align the emotional states of the robot and the human when a specific object is detected in the scene. Pursuing the idea of social interaction based on affect recognition, a first practical application capable of managing the emotional flow is described, involving both conceptual spaces and an emo…
A MOBILE ROBOT FOR TRANSPORT APPLICATIONS IN HOSPITAL DOMAIN WITH SAFE HUMAN DETECTION ALGORITHM
2009
We have been developing a MKR (Muratec Keio Robot), an autonomous omni-directional mobile transfer robot system for hospital applications. This robot has a wagon truck to transfer luggage, important specimens and other materials. This study proposes a safe obstacle collision avoidance technique that includes a human detection algorithm for omni directional mobile robots that realizes a safe movement technology. The robot can distinguish people from others obstacles with human detection algorithm. The robot evades to people more safely by considering its relative position and velocity with respect to them. Some experiments in a hospital were carried out to verify the performance of the human…
Visually-Grounded Language Model for Human-Robot Interaction
2010
Visually grounded human-robot interaction is recognized to be an essential ingredient of socially intelligent robots, and the integration of vision and language increasingly attracts attention of researchers in diverse fields. However, most systems lack the capability to adapt and expand themselves beyond the preprogrammed set of communicative behaviors. Their linguistic capabilities are still far from being satisfactory which make them unsuitable for real-world applications. In this paper we will present a system in which a robotic agent can learn a grounded language model by actively interacting with a human user. The model is grounded in the sense that meaning of the words is linked to a…
Endowing robots with self-modeling abilities for trustful human-robot interactions
2019
Robots involved in collaborative and cooperative tasks with humans cannot be programmed in all their functions. They are autonomous entities acting in a dynamic and often partially known environment. How to interact with the humans and the decision process are determined by the knowledge on the environment, on the other and on itself. Also, the level of trust that each member of the team places in the other is crucial to creating a fruitful collaborative relationship. We hypothesize that one of the main components of a trustful relationship resides in the self-modeling abilities of the robot. The paper illustrates how employing the model of trust by Falcone and Castelfranchi to include self…
A Topic Recognition System for Real World Human-Robot Conversations
2013
One of the main features of social robots is the ability to communicate and interact with people as partners in a natural way. However, achieving a good verbal interaction is a hard task due to the errors on speech recognition systems, and due to the understanting the natural language itself. This paper tries to overcome such kind of problems by presenting a system that enables social robots to get involved in conversation by recognizing its topic. Through the use of classical text mining approach, the presented system allows social robots to understand topics of conversation between human partners, enabling the customization of behaviours in their accordance. The system has been evaluated …
The design of interfaces for multi-robot path planning and control
2014
The field of human-robot interaction has evolved beyond issues concerning the design and development of one person controlling one robot to exploring HRI for groups of robots and teams. Our design research explores biologically-inspired motion that is initiated by a human operator, applied to a single or a small group of robots, and used to affect the motion and path planning of another subset of robots. This exploratory design study first created a taxonomy to categorize individual robot motions, looking at how they could be categorized and used as building blocks. We then combined individual motions with time and velocity as design variables to guide our interaction design. This work led …
Agents in dynamic contexts, a system for learning plans
2020
Reproducing the human ability to cooperate and collaborate in a dynamic environment is a significant challenge in the field of human-robot teaming interaction. Generally, in this context, a robot has to adapt itself to handle unforeseen situations. The problem is runtime planning when some factors are not known before the execution starts. This work aims to show and discuss a method to handle this kind of situation. Our idea is to use the Belief-Desire-Intention agent paradigm, its the Jason reasoning cycle and a Non-Axiomatic Reasoning System. The result is a novel method that gives the robot the ability to select the best plan.
AN EMOTIONAL ROBOTIC PARTNER FOR ENTERTAINMENT PURPOSES
2010
In this paper an emotional humanoid robot based on Latent Semantic Analysis is presented. The robot is capable of interacting and entertain human users through the exhibition of spontaneous and non-repetitive emotional behaviours. The Latent Semantic Analysis (LSA) paradigm, used to encode the semantics of words through a statistical analysis of a large corpus of text, is employed to build an emotional conceptual space that simulates the emotional associative capabilities of human beings, through “Latent Semantic Behaviours”. The LSA paradigm integrates traditional knowledge representation and intuitive capabilities provided by geometric and sub-symbolic information modelling. The effective…
Robot's Inner Speech Effects on Trust and Anthropomorphic Cues in Human-Robot Cooperation
2021
Inner Speech is an essential but also elusive human psychological process which refers to an everyday covert internal conversation with oneself. We argue that programming a robot with an overt self-talk system, which simulates human inner speech, might enhance human trust by improving robot transparency and anthropomorphism. For this reasons, this work aims to investigate if robot’s inner speech, here intended as overt self-talk, affects human trust and anthropomorphism when human and robot cooperate. A group of participants was engaged in collaboration with the robot. During cooperation, the robot talks to itself. To evaluate if the robot’s inner speech influences human trust, two question…
Robotics and Virtual Worlds: An Experiential Learning Lab
2013
Aim of the study was to investigate the cognitive processes involved and stimulated by educational robotics (LEGO® robots and Kodu Game Lab) in lower secondary school students. Results showed that LEGO® and KGL artifacts involve specific cognitive and academic skills. In particular the use of LEGO® is related to deductive reasoning, speed of processing visual targets, reading comprehension and geometrical problem solving; the use of KGL is related to visual-spatial working memory, updating skills and reading comprehension. Both technologies, moreover, are effective in the improvement of visual-spatial working memory. Implications for Human-Robot Interaction and BICA challenge are discussed.