Search results for "human–robot interaction"

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 …

Automation Inner Speech as an Anthropomorphic Feature Affecting Human Trust: Current Issues and Future Directions

2021

This paper aims to discuss the possible role of inner speech in influencing trust in human–automation interaction. Inner speech is an everyday covert inner monolog or dialog with oneself, which is essential for human psychological life and functioning as it is linked to self-regulation and self-awareness. Recently, in the field of machine consciousness, computational models using different forms of robot speech have been developed that make it possible to implement inner speech in robots. As is discussed, robot inner speech could be a new feature affecting human trust by increasing robot transparency and anthropomorphism.

Sensorimotor Communication for Humans and Robots: Improving Interactive Skills by Sending Coordination Signals

2018

During joint actions, humans continuously exchange coordination signals and use nonverbal, sensorimotor forms of communication. Here we discuss a specific example of sensorimotor communication-"signaling"-which consists in the intentional modification of one's own action plan (e.g., a plan for reaching a glass of wine) to make it more predictable or discriminable from alternative action plans that are contextually plausible (e.g., a plan for reaching another glass on the same table). We first review the existing evidence on signaling in human-human interactions, discussing under which conditions humans use signaling. Successively, we distill these insights into a computational theory of sig…

The Inner Life of a Robot in Human-Robot Teaming

2020

Giving the robot a 'human' inner life, such as the capability to think about itself and to understand what the other team members are doing, would increase the efficiency of trustworthy interactions with the other members of the team. Our long-Term research goal is to provide the robot with a computational model of inner life helping the robot to reason about itself, its capabilities, its environment and its teammates. Robot inner speech is a part of the research goal. In this paper, we summarize the results obtained in this direction.

2018

Despite major progress in Robotics and AI, robots are still basically "zombies" repeatedly achieving actions and tasks without understanding what they are doing. Deep-Learning AI programs classify tremendous amounts of data without grasping the meaning of their inputs or outputs. We still lack a genuine theory of the underlying principles and methods that would enable robots to understand their environment, to be cognizant of what they do, to take appropriate and timely initiatives, to learn from their own experience and to show that they know that they have learned and how. The rationale of this paper is that the understanding of its environment by an agent (the agent itself and its effect…

Decoupled nonlinear adaptive control of position and stiffness for pneumatic soft robots

2020

This article addresses the problem of simultaneous and robust closed-loop control of joint stiffness and position, for a class of antagonistically actuated pneumatic soft robots with rigid links and compliant joints. By introducing a first-order dynamic equation for the stiffness variable and using the additional control degree of freedom, embedded in the null space of the pneumatic actuator matrix, an innovative control approach is introduced comprising an adaptive compensator and a dynamic decoupler. The proposed solution builds upon existing adaptive control theory and provides a technique for closing the loop on joint stiffness in pneumatic variable stiffness actuators. Under a very mi…

Perceptual Social Dimensions of Human - Humanoid Robot Interaction

2013

The present paper aims at a descriptive analysis of the main perceptual and social features of natural conditions of agent interaction, which can be specified by agent in human-humanoid robot interaction. A principled approach to human-robot interaction may be assumed to comply with the natural conditions of agents overt perceptual and social behaviour. To validate our research we used the minimalistic humanoid robot Telenoid. We have conducted human-robot interactions test with people with no prior interaction experience with robot. By administrating our questionnaire to subject after well defined experimental conditions, an analysis of significant variance correlation among dimensions in …

Ontology-based state representation for intention recognition in cooperative human-robot environments

2012

In this paper, we describe a novel approach for representing state information for the purpose of intention recognition in cooperative human-robot environments. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. This approach is applied to a manufacturing kitting operation, where humans and robots are working together to develop kits. Based upon a set of predefined high-level states relationships that must be true for future actions to occur, a robot can use the detailed state information presented in this paper to infer the probability of subsequent actions occurring. This would enable the robot to better help th…

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.

Evaluation of Perception Latencies in a Human-Robot Collaborative Environment

2020

The latency in vision-based sensor systems used in human-robot collaborative environments is an important safety parameter which in most cases has been neglected by researchers. The main reason for this neglect is the lack of an accurate ground-truth sensor system with a minimal delay to benchmark the vision-sensors against. In this paper the latencies of 3D vision-based sensors are experimentally evaluated and analyzed using an accurate laser-tracker system which communicates on a dedicated EtherCAT channel with minimal delay. The experimental results in the paper demonstrate that the latency in the vision-based sensor system is many orders higher than the latency in the control and actuat…