Abstract
Team homer@UniKoblenz has become an integral part of the RoboCup@Home community. As such we would like to share our experience gained during the competitions with new teams. In this paper we describe our approaches with a special focus on our demonstration of this year’s finals. This includes semantic exploration, adaptive programming by demonstration and touch enforcing manipulation. We believe that these demonstrations have a potential to influence the design of future RoboCup@Home tasks. We also present our current research efforts in benchmarking imitation learning tasks, gesture recognition and a low cost autonomous robot platform. Our software can be found on GitHub at https://github.com/homer-robotics.
Cite
CITATION STYLE
Memmesheimer, R., Seib, V., Evers, T., Müller, D., & Paulus, D. (2019). Adaptive Learning Methods for Autonomous Mobile Manipulation in RoboCup@Home. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11531 LNAI, pp. 565–577). Springer. https://doi.org/10.1007/978-3-030-35699-6_46
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