Obstacle Avoidance using a Capacitive Skin for Safe Human-Robot Interaction.

Author(s):  
Kamal-Eddine M'Colo ◽  
Bruno Luong ◽  
Andre Crosnier ◽  
Christian Neel ◽  
Philippe Fraisse
Author(s):  
Christopher E. Ábrego

In this manuscript, the development and current state of an inexpensive platform for educational purposes and research in the interaction between humans and robots (human-robot interaction) is described. The platform is based on the ubiquitous LabVIEW programming language and an in-house developed two degree of freedom non-holonomic robot. The platform includes multiple interaction modalities, which will be described, between the robot and the user. The procedures followed for the successful software and hardware implementation are explicated. Furthermore, a demonstration of an obstacle avoidance path planning algorithm for a single obstacle is validated in hardware, as well as simulation demonstration of the multiple obstacle avoidance algorithm. These implementations to the platform further demonstrate the ease of augmenting the existing platform to additional modalities. The algorithm uses a vision acquisition system to identify the location and size of an obstacle, in addition to orientation patterns and calibration points, in the workspace and generate the robot path to reach a desired goal while avoiding the obstacle. The manuscript describes into the current research of path planning in the presence of multiple obstacles. The development of a set of criteria, Generation Succession, Arrival Departure, and Side Consistency, for the algorithm are elucidated in the manuscript. The algorithm has been demonstrated to be successful in simulation by avoiding multiple obstacle in various layouts.


2009 ◽  
Author(s):  
Matthew S. Prewett ◽  
Kristin N. Saboe ◽  
Ryan C. Johnson ◽  
Michael D. Coovert ◽  
Linda R. Elliott

2010 ◽  
Author(s):  
Eleanore Edson ◽  
Judith Lytle ◽  
Thomas McKenna

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.


2019 ◽  
Author(s):  
Cinzia Di Dio ◽  
Federico Manzi ◽  
Giulia Peretti ◽  
Angelo Cangelosi ◽  
Paul L. Harris ◽  
...  

Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. No differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, while 7-years-olds displayed the reverse behavioral pattern, thus highlighting the developing interplay between affective and cognitive correlates of trust.


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