Marco Costanzo

Marco Costanzo

This work is about the extraction of the motion of fingers, in their three articulations, of a keyboard player from a video sequence. The relevance of the problem involves several aspects, in fact, the extraction of the movements of the fingers may be used to compute the keystroke efficiency and individual joint contributions, as showed by Werner Goebl and Caroline Palmer in the paper 'Temporal Control and Hand Movement Efficiency in Skilled Music Performance'. Those measures are directly related to the precision in timing and force measures. A very good approach to the hand gesture recognition problem has been presented in the paper ' Real-Time Hand Gesture Recognition Using Finger Segmentation'. Detecting the keys pressed on a keyboard is a task that can be complex because of the shadows that can degrade the quality of the result and possibly cause the detection of not pressed keys. Among the several approaches that already exist, a great amount of them is based on the subtraction of frames in order to detect the movements of the keys caused by their pressure. Detecting the keys that are pressed could be useful to automatically evaluate the performance of a pianist or to automatically write sheet music of the melody that is being played.

Marco Costanzo, Simon Stelter, Ciro Natale et al.

Manipulation planning and control are relevant building blocks of a robotic system and their tight integration is a key factor to improve robot autonomy and allows robots to perform manipulation tasks of increasing complexity, such as those needed in the in-store logistics domain. Supermarkets contain a large variety of objects to be placed on the shelf layers with specific constraints, doing this with a robot is a challenge and requires a high dexterity. However, an integration of reactive grasping control and motion planning can allow robots to perform such tasks even with grippers with limited dexterity. The main contribution of the paper is a novel method for planning manipulation tasks to be executed using a reactive control layer that provides more control modalities, i.e., slipping avoidance and controlled sliding. Experiments with a new force/tactile sensor equipping the gripper of a mobile manipulator show that the approach allows the robot to successfully perform manipulation tasks unfeasible with a standard fixed grasp.