Adaptive Synergies for the Design and Control of the Pisa/IIT SoftHand

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 1 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 multimedia extensio

The SoftHand Pro: Translation from Robotic Hand to Prosthetic Prototype

This work presents the translation from a humanoid robotic hand to a prosthetic prototype and its first evaluation in a set of 9 persons with amputation. The Pisa/IIT SoftHand is an underactuated hand built on the neuroscientific principle of motor synergies enabling it to perform natural, human-like movements and mold around grasped objects with minimal control input. These features motivated the development of the SoftHand Pro, a prosthetic version of the SoftHand built to interface with a prosthetic socket. The results of the preliminary testing of the SoftHand Pro showed it to be a highly functional design with an intuitive control system. Present results warrant further testing to develop the SoftHand Pro

Preliminary results toward continuous and proportional control of a multi-synergistic soft prosthetic hand

State of art of modern hand prosthesis is populated by sophisticate hi-tech poly-articular hands which usually offer a broader set of movement capabilities, with the possibility to control up to 4 or 5 motors and achieve several different postures. Unfortunately these device are not so easy to control. A novel emerging trend is oriented towards a strong simplification of the mechanical design (through i.e. underactuation mechanisms), but still maintaining a good level of performance. A successful example is the SoftHand2 Pro, a 19 Degrees of Freedom (DoF) anthropomorphic hand which, using two motors, can move along two different synergistic directions, to perform either power grasp, precision grasp and index point. The combination of this multi-synergistic prosthetic hand with advanced controls, as myoelectric pattern recognition algorithms, allows to get promising results toward a more natural and intuitive control, introducing novel features as the possibility of a continuous switch between gestures. Preliminary experimental results are presented, demonstrating the effectiveness of the idea

Editorial: Mapping human sensory-motor skills for manipulation onto the design and control of robots

Editorial on the Research Topic Mapping Human Sensory-Motor Skills for Manipulation Onto the Design and Control of Robot

Editorial: Mapping Human Sensory-Motor Skills for Manipulation Onto the Design and Control of Robots

The extraordinary human sensory-motor capabilities arise from the interaction with the external world and the interplay of different elements, which are controlled within a space whose dimensionality is lower than the available number of dimensions, as suggested by the concept of synergies, see (e.g., Turvey, 2007; Latash, 2008; Santello et al., 2013). This general simplification approach has then been successfully used in robotics, to inform the development of simple yet effective artificial devices, see (e.g., Santello et al., 2016). Mutual inspiration between robotics and neuroscience could hence be the key to advance both these disciplines: through a bio-aware approach for the design of mechatronic systems, on one side, and the deployment of technical tools for novel neuroscientific experiments, on the other. The manuscripts presented in this e-book shed light on the organization of human sensory-motor architecture, presenting instruments and mechatronic systems that can be successfully applied to neuroscientific investigation. At the same time, we report on robotic translations of neuroscientific outcomes

Influence of force feedback on grasp force modulation in prosthetic applications: A preliminary study

In typical movement, humans use a combination of feed-forward and feedback motor control strategies to interact with the world around them. However, when sensory input is impaired or absent, as in the case of various neuropathies or amputation, the ability to perform everyday tasks, like modulating grip force to object weight, can be affected. In this study, we show the results of a preliminary study using a pressure cuff-like force feedback device (CUFF) with the SoftHand Pro (SHP) prosthetic hand. Subjects lifted an object of various weights using their own hand, with the SHP without feedback, and the SHP with force feedback. As expected, significant differences were found between the two SHP conditions and the native hand, but surprisingly not between the SHP conditions. A closer look at the data suggests the feedback may help diminish the overall grip force used during grasping even if it does not alter the grip force modulation to object weight. The lack of significance may be due in part to high intra- and inter-subject variability. Additional training with the CUFF and/or customization of the feedback may enhance the effects and warrants further stud

Synergy-driven performance enhancement of vision-based 3D hand pose reconstruction

In this work we propose, for the first time, to improve the performance of a Hand Pose Reconstruction (HPR) technique from RGBD camera data, which is affected by self-occlusions, leveraging upon postural synergy information, i.e., a priori information on how human most commonly use and shape their hands in everyday life tasks. More specifically, in our approach, we ignore joint angle values estimated with low confidence through a vision-based HPR technique and fuse synergistic information with such incomplete measures. Preliminary experiments are reported showing the effectiveness of the proposed integration

From humans to robots: The role of cutaneous impairment in human environmental constraint exploitation to inform the design of robotic hands

Human hands are capable of a variety of movements, thanks to their extraordinary biomechanical structure and relying on the richness of human tactile information. Recently, soft robotic hands have opened exciting possibilities and, al the same time, new issues related to planning and control. In this work, we propose to study human strategies in environmental constraint exploitation to grasp objects from a table. We have considered both the case where participants' fingertips were free and with a rigid shell worn on them to understand the role of cutaneous touch. Main kinematic strategies were quantified and classified in an unsupervised manner. The principal strategies appear to be consistent in both experimental conditions, although cluster cardinality differs. Furthermore, as expected, tactile feedback improves both grasp precision and quality performance. Results opens interesting perspective for sensing and control of soft manipulators

Supervised Autonomous Locomotion and Manipulation for Disaster Response with a Centaur-like Robot

Mobile manipulation tasks are one of the key challenges in the field of search and rescue (SAR) robotics requiring robots with flexible locomotion and manipulation abilities. Since the tasks are mostly unknown in advance, the robot has to adapt to a wide variety of terrains and workspaces during a mission. The centaur-like robot Centauro has a hybrid legged-wheeled base and an anthropomorphic upper body to carry out complex tasks in environments too dangerous for humans. Due to its high number of degrees of freedom, controlling the robot with direct teleoperation approaches is challenging and exhausting. Supervised autonomy approaches are promising to increase quality and speed of control while keeping the flexibility to solve unknown tasks. We developed a set of operator assistance functionalities with different levels of autonomy to control the robot for challenging locomotion and manipulation tasks. The integrated system was evaluated in disaster response scenarios and showed promising performance.Comment: In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 201