Experimental evaluation of Postural Synergies during Reach to Grasp with the UB Hand IV Fanny Ficuciello 1 , Gianluca Palli 2 , Claudio Melchiorri 2 and Bruno Siciliano 1 Abstract— In this paper, the postural synergies configuration subspace given by the fundamental eigengrasps of the UB Hand IV (University of Bologna Hand, version IV) is derived through experiments. This study is based on the kinematic structure of the robotic hand and on the taxonomy of the grasps of common objects. Experimental results show that it is possible to obtain grasp synthesis for a large set of objects both in the case of precision or power grasps by using only a very limited set of dominant eigengrasps. The tasks here presented are planned with an initial hold of the hand followed by reach and grasp phases, that are unique for each object/grasp combination, during which the robotic hand posture evolves continuously within a subset of the hand configuration space given by the two predominant eigenpostures. The paper reports the method adopted to define from experiments the postural synergies for the UB Hand IV and the results of the grasp tasks performed adopting the defined synergies. I. I NTRODUCTION One of the greatest challenges of humanoid robotics is to provide robotic systems with autonomous and dextrous skills. Since the next generation of robots will interact with people directly, the robot of the future must be thought of heaving human excellence. Therefore, the interest on replicating the human manipulation abilities is growing among researchers. To reproduce human-like grasping and manipulation abil- ities, complex dexterous hands with advanced sensorimotor skills and human-like kinematics are needed. Moreover, the implementation of control algorithms for anthropomorphic robotic hands able to reproduce human-like manipulation abilities is actually an hard problem. Therefore, the research is going towards the reproduction of human grasping capa- bilities not only by means of anthropomorphic design but also by adopting human-inspired control strategies. The studies on grasp taxonomy carried out by scientists as Napier [1], Cutkosky [2] and Iberall [3] aim to define which fingers (and which parts of the fingers) are used by humans to generate forces on the grasped object. According to this criterion, the hand configuration during grasp operations can be decomposed in a limited set of basic postures. Nevertheless, recent advances in neuroscience have shown 1 Dipartimento di Informatica e Sistemistica, Universit` a di Napoli Federico II, 80125 Napoli, Italy, email: {fanny.ficuciello, bruno.siciliano}@unina.it. 2 Dipartimento di Elettronica, Informatica e Sistemistica, Univer- sit` a di Bologna, 40136 Bologna, Italy,email: {gianluca.palli, clau- dio.melchiorri}@unibo.it. This research has been partially funded by the EC Seventh Framework Programme (FP7) under grant agreement no. 216239 as part of the IP DEXMART (DEXterous and autonomous dual-arm/hand robotic manipu- lation with sMART sensory-motor skills: A bridge from natural to artificial cognition). Fig. 1. The UB Hand IV prototype. that the control of human hand during grasp is dominated by movements in a continuous configuration space of highly reduced dimensionality with respect to number of degrees of freedom of the human hand. In [4] the principal component analysis (PCA) has been used to calculate the postural syn- ergies from real-world data collected on a variety of human hand postures. Moreover, the authors show that a wide set of hand postures during grasp operations evolves continuously within a linear space spanned by few postural synergies that account for most of the hand configurations variance, without distinguishing between power and precision grasps. The combination of tendon coupling and muscle activation patterns exhibited by humans lead to significant joint cou- pling and inter-finger coordination, or, in other words, to postural synergies, that are evidence of simplified control schemes occurring at neurological level for the organization of the hand movements. In [5] it is shown that even if higher principal components account for a small percentage of the variance, they give crit- ical details not only for the static grasp when the hand adapts to the object shape, but also for the act of preshaping during the grasp. In [6], [7], [8] the authors extend the concept of postural synergies to robotic hands showing how a similar dimensionality reduction can be used to derive comprehen- sive planning and controlling algorithms that produce stable grasps for a number of different complex hand models. Other applications has been made in order to simplify the design and the analysis of robotic hand structures [9]. In [10] the authors investigate how the number and types of synergies are related to the possibility of controlling the contact forces and the object motion in grasping and manipulation tasks. In [11], using the definition of force-closure for underactuated 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems September 25-30, 2011. San Francisco, CA, USA 978-1-61284-456-5/11/$26.00 ©2011 IEEE 1775