title: Recent Data Sets on Object Manipulation: A Survey.
abstract: Data sets is crucial not only for model learning and evaluation but also to advance knowledge on human behavior, thus fostering mutual inspiration between neuroscience and robotics. However, choosing the right data set to use or creating a new data set is not an easy task, because of the variety of data that can be found in the related literature. The first step to tackle this issue is to collect and organize those that are available. In this work, we take a significant step forward by reviewing data sets that were published in the past 10 years and that are directly related to object manipulation and grasping. We report on modalities, activities, and annotations for each individual data set and we discuss our view on its use for object manipulation. We also compare the data sets and summarize them. Finally, we conclude the survey by providing suggestions and discussing the best practices for the creation of new data sets.
authors.affiliation: 1 Department of Computer Science and Engineering, University of South Florida , Tampa, Florida.
authors.forename: Yongqiang
authors.initials: Y
authors.lastname: Huang
authors.affiliation: 2 Research Center "E. Piaggio," Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy .
authors.forename: Matteo
authors.initials: M
authors.lastname: Bianchi
authors.affiliation: 3 School of Engineering and Applied Science, Yale University , New Haven, Connecticut.
authors.forename: Minas
authors.initials: M
authors.lastname: Liarokapis
authors.affiliation: 1 Department of Computer Science and Engineering, University of South Florida , Tampa, Florida.
authors.forename: Yu
authors.initials: Y
authors.lastname: Sun
keywords: data collection; data set; learning; robotic grasping; robotic manipulation; robotics