[PAST] Synergies and underactuation: learning and control strategies for anthropomorphic hands
[PAST] Synergies and underactuation: learning and control strategies for anthropomorphic hands [2,239]
2016 / 10 / 10 AM 11:00
Location: 301 - 1420
Speaker: Dr. Fanny Ficuciello
Fanny Ficuciello received the Laurea degree magna cum laude in Mechanical Engineering from the University of Naples Federico II in 2007. She received the Ph.D. degree in Computer and Automation Engineering at the University of Naples Federico II, in November 2010. Currently she is holding a Post Doctoral position at the University of Naples Federico II. Her research activity is focused on biomechanical design and bio-aware control strategies for anthropomorphic artificial hands, grasping and manipulation with hand/arm and dual arm robotic systems, human-robot interaction control, variable impedance control and redundancy resolution strategies. Recently she is involved also on surgical robotics research projects, as a member of the ICAROS center (Interdepartmental Center for Advances in Robotic Surgery) of the University of Naples Federico II. She has published more than 30 journal and conference papers and book chapters on planning and control strategies based on postural synergies, supervised learning and reinforcement learning techniques for anthropomorphic hands; impedance based control strategies for hand/arm and dual arm robotic systems and intentional-aware human-robot interaction.
New generation of robots should have comparable abilities to deftly move in different environments, autonomously learn and make decisions. The use of anthropomorphic hands has become a key breakthrough in advanced robotics involving both humanoid robots and prosthetic applications. An efficient and forefront design of advanced robotic hands requires solving a compromise among size and weight, functional dexterity and control complexity. Advanced mechatronic structure and high number of degrees of freedoms (DoFs) are essential to change different configurations and adapt to the environment.
On the other hand, design and control complication due to high DoF can be somewhat offset by means of coordinated motion that help to simplify robot hardware and software. This can be summarized by saying that the robot must be equipped with embodied intelligence. A solution to the problem can be found in designing underactuated devices and comes down to choosing the optimal number of motors as well as the motion couplings between fingers and joints. However, underactuated hands require the investigation of planning and control methods that disregard accurate definition of the desired contact points on the object and guarantee robustness with respect to variability of shape and size. To overcome these problems, synergies concept is used to develop control and learning algorithms. The synergy concept is useful for innovative underactuated design of anthropomorphic hands and is a powerful tool to plan grasps and control artificial hands both fully-actuated and underactuated, i.e. already provided of their own mechanical synergies. Fanny Ficuciello’s contribution to this topic is presented and divided in three parts concerning synergies computation, control and learning. Those parts are different aspects of the same research that goes towards the realization of human-like prehensile capabilities and autonomous learning skills for a robotic upper limb system with anthropomorphic design.