Soft robotics and under-actuation were recently demonstrated as good approaches for the implementation of humanoid robotic hands. Nevertheless, it is often difficult to increase the number of degrees of actuation of heavily under-actuated hands without compromising their intrinsic simplicity. In this paper we analyze the Pisa/IIT SoftHand and its underlying logic of adaptive synergies, and propose a method to double its number of degree of actuation, with a very reduced impact on its mechanical complexity. This new design paradigm is based on constructive exploitation of friction phenomena. Based on this method, a novel prototype of under-actuated robot hand with two degrees of actuation is proposed, named Pisa/IIT SoftHand+. A preliminary validation of the prototype follows, based on grasping and manipulation examples of some objects.

Automated handling of heavy deformable goods, due to their challenging material properties, sets a benchmark for handling sacks, such as bags of fabrics, synthetic packings, papers filled with coffee, cereals and plastic pellets. The paper focuses on the handling of jute coffee sacks.Nowadays the manipulation of jute coffee sacks is performed manually, because of the lack of specific grippers able to grasp this type of object. Hence, a set of concepts have been designed and developed to test the functionality of new devices, specifically intended to be used for the grasping of jute coffee sacks. Grippers have then been ranked through a Multiple Attribute Decision Making (MADM) method, in order to identify the best gripping tools for the handling of non-rigid materials. Finally, one of the most promising grippers has been designed and tested on real scale jute coffee sacks.

This chapter presents the hardware, software and overall strategy used by the team UNIPI-IIT-QB to participate to the Robotic Grasping and Manipulation Competition. It relies on the PISA/IIT Soft-Hand, which is underactuated soft robotic hand that can adapt to the grasped object shape and is compliant with the environment. It was used for the hand-in-hand and for the simulation tracks, where the team reached first and third places respectively.