10.1109/HUMANOIDS47582.2021.9555800
https://zenodo.org/records/6815122
oai:zenodo.org:6815122
Jingyi Liu
Jingyi Liu
University College London
Pietro Balatti
Pietro Balatti
0000-0001-8303-9733
Istituto Italiano di Tecnologia
Kirsty Ellis
Kirsty Ellis
University College London
Denis Hadjivelichkov
Denis Hadjivelichkov
University College London
Danail Stoyanov
Danail Stoyanov
University College London
Arash Ajoudani
Arash Ajoudani
0000-0002-1261-737X
Istituto Italiano di Tecnologia
Dimitrios Kanoulas
Dimitrios Kanoulas
0000-0002-3684-1472
University College London
Garbage Collection and Sorting with a Mobile Manipulator using Deep Learning and Whole-Body Control
Zenodo
2021
Mobile manipulation
2021-10-11
https://zenodo.org/communities/h2020-sophia
https://zenodo.org/communities/eu
Creative Commons Attribution 4.0 International
Domestic garbage management is an important aspect of a sustainable environment. This paper presents a novel garbage classification and localization system for grasping and placement in the correct recycling bin, integrated on a mobile manipulator. In particular, we first introduce and train a deep neural network (namely, GarbageNet) to detect different recyclable types of garbage. Secondly, we use a grasp localization method to identify a suitable grasp pose to pick the garbage from the ground. Finally, we perform grasping and sorting of the objects by the mobile robot through a whole-body control framework. We experimentally validate the method, both on visual RGB-D data and indoors on a real full-size mobile manipulator for collection and recycling of garbage items placed on the ground.
European Commission
10.13039/501100000780
871237
Socio-physical Interaction Skills for Cooperative Human-Robot Systems in Agile Production