Cooperative human robot interaction systems: IV. Communication of shared plans with Naïve humans using gaze and speech

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Benchmarking neuromorphic vision: Lessons learnt from computer vision

10.3389/fnins.2015.00374Frontiers in Neuroscience9OCT37

Shared Presence and Collaboration Using a Co-Located Humanoid Robot

This work proposes the concept of shared presence, where we enable a user to “become” a co-located humanoid robot while still being able to use their real body to complete tasks. The user controls the robot and sees with its vision and sen-sors, while still maintaining awareness and use of their real body for tasks other than controlling the robot. This shared presence can be used to accomplish tasks that are difficult for one person alone, for example, a robot manipulating a circuit board for easier soldering by the user, lifting and manipulat-ing heavy or unwieldy objects together, or generally having the robot conduct and complete secondary tasks while the user focuses on the primary tasks. If people are able to over-come the cognitive difficulty of maintaining presence for both themselves and a nearby remote entity, tasks that typi-cally require the use of two people could simply require one person assisted by a humanoid robot that they control. In this work, we explore some of the challenges of creating such a system, propose research questions for shared presence, and present our initial implementation that can enable shared presence. We believe shared presence opens up a new re-search direction that can be applied to many fields, including manufacturing, home-assistant robotics, and educationN

Consensus Driven Self-Organization: Towards Non Hierarchical Multi-Map Architectures

International audienceThis paper introduces CxSOM, a model to build modular architectures based on self-organizing maps (SOM). An original consensus driven approach enables to adress non-hierarchical architectures where SOMs get organized jointly. The paper aims at showing how the modules are able to store the association between data, and evaluating, by a mutual information criterion, the resulting organization. These results stand as preliminary work to study bigger architectures

From Motor Learning to Interaction Learning in Robots

This paper is a slightly adapted version of the Introduction chapter of a book “From Motor t