Affiliations: Institut für Informatik, LFG Künstliche Intelligenz, Humboldt-Universität zu Berlin, Germany. mellmann@informatik.hu-berlin.de | Robotics and Biology Laboratory, School of Electrical Engineering and Computer Science, Technische Universität, Berlin, Germany. giuseppe@mailbox.tu-berlin.de
Note: [] Address for correspondence: Institut für Informatik, LFG Künstliche Intelligenz, Humboldt-Universität zu Berlin, Germany The authors are grateful to the members of the Nao Team Humboldt for technical support and also to Manfred Hild and Philipp Hähnel for inspiring discussions.
Note: [] Both authors contributed equally to this paper.
Abstract: The ability to grasp objects of different size and shape is one of the most important skills of a humanoid robot. There are a lot of different approaches tackling this problem; however, there is no general solution. The complexity and the skill of a possible grasping motion depend hardly on a particular robot. In this paper we analyze the kinematic and sensory grasping abilities of the humanoid robot Nao. Its kinematic constraints and hand's mechanical structure represent an interesting case of study due to lack of actuators for fingers and the limited computation power. After describing the platform and studying its capabilities, we propose some simple controllers and we present a benchmark based on some experimental data.
