Florian Kagerer, Maximilian Beinhofer, Stefan Stricker, A. Nüchter
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BED-BPP: Benchmarking dataset for robotic bin packing problems
Many algorithms that were developed for solving three-dimensional bin packing problems use generic data for either experiments or evaluation. However, none of these datasets became accepted for benchmarking 3D bin packing algorithms throughout the community. To close this gap, this paper presents the benchmarking dataset for robotic bin packing problems (BED-BPP), which is based on realistic data. We show the variety of the dataset by elaborating an n-gram analysis. Besides, we propose an evaluation function, which contains a stability check that uses rigid body simulation. We demonstrated the application of our dataset on four different approaches, which we integrated in our software environment.
期刊介绍:
The International Journal of Robotics Research (IJRR) has been a leading peer-reviewed publication in the field for over two decades. It holds the distinction of being the first scholarly journal dedicated to robotics research.
IJRR presents cutting-edge and thought-provoking original research papers, articles, and reviews that delve into groundbreaking trends, technical advancements, and theoretical developments in robotics. Renowned scholars and practitioners contribute to its content, offering their expertise and insights. This journal covers a wide range of topics, going beyond narrow technical advancements to encompass various aspects of robotics.
The primary aim of IJRR is to publish work that has lasting value for the scientific and technological advancement of the field. Only original, robust, and practical research that can serve as a foundation for further progress is considered for publication. The focus is on producing content that will remain valuable and relevant over time.
In summary, IJRR stands as a prestigious publication that drives innovation and knowledge in robotics research.