Hands in the Real World

Robots face a rapidly expanding range of potential applications beyond controlled environments, from remote exploration and search-and-rescue to household assistance and agriculture. The focus of physical interaction is typically delegated to end-effectors -- fixtures, grippers or hands -- as these machines perform manual tasks. Yet, effective deployment of versatile robot hands in the real world is still limited to few examples, despite decades of dedicated research. In this paper we review hands that found application in the field, aiming to discuss open challenges with more articulated designs, discussing novel trends and perspectives. We hope to encourage swift development of capable robotic hands for long-term use in varied real world settings. The first part of the paper centers around progress in artificial hand design, identifying key functions for a variety of environments. The final part focuses on the overall trends in hand mechanics, sensors and control, and how performance and resiliency are qualified for real world deployment

Wearable Integrated Soft Haptics in a Prosthetic Socket

Modern active prostheses can be used to recover part of the motor function associated with the loss of a hand. Nevertheless, most sensory abilities are lost, and the person has to manage interaction by relying mostly on visual feedback. Despite intensive research devoted to convey touch related cues, very few solutions have been integrated in a real prosthesis worn by a user. This letter describes a soft pneumatic feedback system designed with integrability and wearability among its main concerns. At the system core, two soft pneumatic actuators are placed in contact with the subject's skin and inflated to provide pressure stimuli, which can be used to represent force exerted by the hand grasping. We report on the design and the characterization of the system, including behavioural experiments with able-bodied participants and one prosthesis user. Results from psychophysical, dexterity and usability tests show that the system has the potential to restore sensory feedback in hand amputees, and can be a useful tool for enabling a correct modulation of the force during grasping and manipulation tasks

On the motion/stiffness decoupling property of articulated soft robots with application to model-free torque iterative learning control

This paper tackles the problem of controlling articulated soft robots (ASRs), i.e., robots with either fixed or variable elasticity lumped at the joints. Classic control schemes rely on high-authority feedback actions, which have the drawback of altering the desired robot softness. The problem of accurate control of ASRs, without altering their inherent stiffness, is particularly challenging because of their complex and hard-to-model nonlinear dynamics. Leveraging a learned anticipatory action, Iterative Learning Control (ILC) strategies do not suffer from these issues. Recently, ILC was adopted to perform position control of ASRs. However, the limitation of position-based ILC in controlling variable stiffness robots is that whenever the robot stiffness profile is changed, a different input action has to be learned. Our first contribution is to identify a wide class of ASRs, whose motion and stiffness adjusting dynamics can be proved to be decoupled. This class is described by two properties that we define: strong elastic coupling - relative to motors and links of the system, and their connections - and homogeneity - relative to the characteristics of the motors. Furthermore, we design a torque-based ILC scheme that, starting from a rough estimation of the system parameters, refines the torque needed for the joint positions tracking. The resulting control scheme requires minimum knowledge of the system. Experiments on variable stiffness robots prove that the method effectively generalizes the iterative procedure w.r.t. the desired stiffness profile and allows good tracking performance. Finally, potential restrictions of the method, e.g., caused by friction phenomena, are discussed

The Rice Haptic Rocker: Skin stretch haptic feedback with the Pisa/IIT SoftHand

Touch provides an important cue to perceive the physical properties of the external objects. Recent studies showed that tactile sensation also contributes to our sense of hand position and displacement in perceptual tasks. In this study, we tested the hypothesis that, sliding our hand over a stationary surface, tactile motion may provide a feedback for guiding hand trajectory. We asked participants to touch a plate having parallel ridges at different orientations and to perform a self-paced, straight movement of the hand. In our daily-life experience, tactile slip motion is equal and opposite to hand motion. Here, we used a well-established perceptual illusion to dissociate, in a controlled manner, the two motionestimates. According to previous studies, this stimulus produces a bias in the perceived direction of tactile motion, predicted by tactile flow model. We showed a systematic deviation in the movement of the hand towards a direction opposite to the one predicted by tactile flow, supporting the hypothesis that touch contributes to motor control of the hand. We suggested a model where the perceived hand motion is equal to a weighted sum of the estimate from classical proprioceptive cues (e.g., from musculoskeletal system) and the estimate from tactile slip

BRL/Pisa/IIT SoftHand:A Low-cost, 3D-Printed, Underactuated, Tendon-Driven Hand with Soft and Adaptive Synergies

This letter introduces the SRI/Pisa/HT (BPI) SoftHand: a single actuator-driven, low-cost, 3D-printed, tendondriven, underactuated robot hand that can be used to perform a range of grasping tasks. Based on the adaptive synergies of the Pisa/IIT SoftHand, we design a new joint system and tendon routing to facilitate the inclusion of both soft and adaptive synergies, which helps us balance durability, affordability and grasping performance of the hand. The focus of this work is on the design, simulation, synergies and grasping tests of this SoftHand. The novel phalanges are designed and printed based on linkages, gear pairs and geometric restraint mechanisms, and can be applied to most tendon-driven robotic hands. We show that the robot hand can successfully grasp and lift various target objects and adapt to hold complex geometric shapes, reflecting the successful adoption of the soft and adaptive synergies. We intend to open-source the design of the hand so that it can be built cheaply on a home 3D-printer

Variable stiffness control for oscillation damping

In this paper a model-free approach for damping control of Variable Stiffness Actuators is proposed. The idea is to take advantage of the possibility to change the stiffness of the actuators in controlling the damping. The problem of minimizing the terminal energy for a one degree of freedom spring-mass model with controlled stiffness is first considered. The optimal bang-bang control law uses a maximum stiffness when the link gets away from the desired position, i.e. the link velocity is decreasing, and a minimum one when the link is going towards it, i.e. the link velocity is increasing. Based on Lyapunov stability theorems the obtained law has been proved to be stable for a multi-DoF system. Finally, the proposed control law has been tested and validated through experimental tests

Computed Torque Control for a VSA type Hybrid Shoulder Joint

Robotic anthropomorphism has been the study area of many researchers, which led to the conclusion that perceiving similar human features allow robots to be more socially accepted and integrated. Anthropomorphism can be thought from both morphological and functional point of views, while the degree of integration of both aspects determines the social impact of their union. One key aspect to the embodiment of functional anthropomorphism in robots is the impedance modulation. In this work, we present the first prototype of a variable stiffness actuated, hybrid type, robotic shoulder joint. We leverage our work on the anthropomorphic approach presented in our previous works for humanoids and humans applications. We then formulate the computed torque control scheme for such systems, controlled in fully autonomous scenarios

Dynamic Morphological Computation Through Damping Design of Soft Continuum Robots

Inspired by nature, soft robotics aims at enhancing robots capabilities through the use of soft materials. This article presents the study of soft continuum robots which can change their dynamic behavior thanks to a proper design of their damping properties. It enables an under-actuated dynamic strategy to control multi-chamber pneumatic systems using a reduced number of feeding lines. The present work starts from the conceptual investigation of a way to tune the damping properties of soft continuum robots, and leverages on the introduction of viscous fluid within the soft chamber wall to produce dissipative actions. Several solutions are analyzed in simulations and the most promising one is tested experimentally. The proposed approach employs a layer of granular material immersed in viscous silicone oil to increase the damping effect. After validation and experimental characterization, the method is employed to build soft continuum actuators with different deformation patterns, i.e., extending, contracting and bending. Experimental results show the dynamic behavior of the presented actuators. Finally, the work reports information on how the actuators are designed and builded, together with a discussion about possible applications and uses