RoboCup@Home Education 2020 Best Performance: RoboBreizh, a modular approach
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 25 references that are in the map. First posted on arXiv 7 Jul 2021.
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References · 9
- 2014Microsoft COCO: Common Objects in Contextcited by 17,608
- 2017Mask R-CNNcited by 7,277
- 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
- 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,162
- 2018OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,162
- 2017ROS Navigation Tuning Guidecited by 9
- 2019Trends, Challenges and Adopted Strategies in RoboCup@Homecited by 4
- 2019qiBullet, a Bullet-based simulator for the Pepper and NAO robotscited by 2
- 2017Setting Up Pepper For Autonomous Navigation And Personalized Interaction With Userscited by 1
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