Adaptive synergies for the design and control of the Pisa/IIT SoftHand

Abstract

In this paper we introduce the Pisa/IIT SoftHand, a novel robot hand prototype designed with the purpose of being robust and easy to control as an industrial gripper, while exhibiting high grasping versatility and an aspect similar to that of the human hand. In the paper we briefly review the main theoretical tools used to enable such simplification, i.e. the neuroscience-based notion of soft synergies. A discussion of several possible actuation schemes shows that a straightforward implementation of the soft synergy idea in an effective design is not trivial. The approach proposed in this paper, called adaptive synergy, rests on ideas coming from underactuated hand design. A synthesis method to realize a desired set of soft synergies through the principled design of adaptive synergy is discussed. This approach leads to the design of hands accommodating in principle an arbitrary number of soft synergies, as demonstrated in grasping and manipulation simulations and experiments with a prototype. As a particular instance of application of the synthesis method of adaptive synergies, the Pisa/IIT SoftHand is described in detail. The hand has 19 joints, but only uses one actuator to activate its adaptive synergy. Of particular relevance in its design is the very soft and safe, yet powerful and extremely robust structure, obtained through the use of innovative articulations and ligaments replacing conventional joint design. The design and implementation of the prototype hand are shown and its effectiveness demonstrated through grasping experiments, reported also in the multimedia extension 1.

Exploitation of Environmental Constraints in Human and Robotic Grasping

“…The SDM hand (Dollar and Howe, 2010), the Velo gripper (Ciocarlie et al, 2013), the i-HY hand (Odhner et al, 2014), and the Pisa/IIT SoftHand (Catalano et al, 2014) couple the actuation of degrees of freedom using tendonpulley systems, adapting the shape of the hand to the object while equalizing contact forces.…”

A Fabric-Based Approach for Wearable Haptics

“…The motors can spin in opposite directions to tighten or loosen the band on the arm, thus conveying normal force and pressure cues; they can also spin in the same direction in order to slide the band around the arm, thus inducing skin stretch cues that can easily be associated with directional and navigation information (see Figure 5). In the first mode, CUFF was used in association with Pisa/IIT SoftHand (SH), an anthropomorphic robotic hand, actuated through a single motor, but capable of adapting for grasping different objects [64]. Because the SH has no built-in force sensors, an estimation of applied force can be obtained based on the current the motor draws.…”

“…This is because residual current is proportional to grasp force (see Figure 6). This approach is motivated by the fact that there is a net difference in the In the first mode, CUFF was used in association with Pisa/IIT SoftHand (SH), an anthropomorphic robotic hand, actuated through a single motor, but capable of adapting for grasping different objects [64]. Because the SH has no built-in force sensors, an estimation of applied force can be obtained based on the current the motor draws.…”

Grasping and Manipulation of Unknown Objects Based on Visual and Tactile Feedback

“…Employing the outlined control basis framework to realize approaching motions for grasping and exploiting the passive compliance of modern, often underactuated hands [18,19], grasp planning is extremely simplified: The fingers will automatically wrap around the object due to the inherent compliance of the hand. Thus, the only task for grasp planning is to choose a suitable grasp prototype and to align the hand to the object during the approach phase.…”