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RoboCup@Home Education 2020 Best Performance: RoboBreizh, a modular approach

2021-07-07 02:09:37
Antoine Dizet, Cédric Le Bono, Amélie Legeleux, Maëlic neau, Cédric Buche
arXiv_AI
               
Abstract

Every year, the Robocup@Home competition challenges teams and robots' abilities. In 2020, the RoboCup@Home Education challenge was organized online, altering the usual competition rules. In this paper, we present the latest developments that lead the RoboBreizh team to win the contest. These developments include several modules linked to each other allowing the Pepper robot to understand, act and adapt itself to a local environment. Up-to-date available technologies have been used for navigation and dialogue. First contribution includes combining object detection and pose estimation techniques to detect user's intention. Second contribution involves using Learning by Demonstrations to easily learn new movements that improve the Pepper robot's skills. This proposal won the best performance award of the 2020 RoboCup@Home Education challenge.

Abstract (translated)

URL

https://arxiv.org/abs/2107.02978

PDF

https://arxiv.org/pdf/2107.02978.pdf

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