RoboCup@Home Education 2020 Best Performance: RoboBreizh, a modular approach
This work addresses the problem of enhancing robot capabilities for specific competition scenarios, representing an incremental improvement in robotics for educational challenges.
The paper tackled the challenge of adapting a robot for the online RoboCup@Home Education competition by developing modular systems for understanding, acting, and adapting in local environments, resulting in the RoboBreizh team winning the best performance award in 2020.
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.