Supernumerary robotic limbs (SRLs) are wearable robots designed to enhance the sensorimotor abilities of humans. SRLs can be used to compensate for lost functions in patients with motor deficits and, more in general, to augment the sensorimotor capabilities of humans to interact with the environment. The design and control of SRLs present several challenges. SRLs must have high levels of ergonomics and wearability and, depending on the application, they might also require enhanced robustness and strength. Supernumerary robotics differs from collaborative robotics, since SRLs are not collaborative external agents but rather act under the direct command of the operator who, thanks to the use of suitable interfaces, gains the control of some actions of the SRLs. From the control point of view, it is fundamental to find the right trade-off between the degrees of freedom that are under the direct control of the user and the level of robot autonomy. The adoption of feedback interfaces can help the human to better command and use the SRL. In this review, we discuss all these aspects, relating them to the current literature on SRLs. We also present the main applications and the potential of these relatively recent devices, as well as the main neuroscientific questions they rise on the implications of their use on the users’ body schema.

In industrial scenarios, requiring human-robot collaboration, the understanding between the human operator and his/her robot coworker is paramount. On the one side, the robot has to detect human intentions, and on the other side, the human needs to be aware of what is happening during the collaborative task. In this letter, we address the first issue by predicting human behavior through a new recursive Bayesian classifier, exploiting head, and hand tracking data. Human awareness is tackled by endowing the human with a vibrotactile ring that sends acknowledgments to the user during critical phases of the collaborative task. The proposed solution has been assessed in a human-robot collaboration scenario, and we found that adding haptic feedback is particularly helpful to improve the performance when the human-robot cooperation task is performed by nonskilled subjects. We believe that predicting operator's intention and equipping him/her with wearable interface, able to give information about the prediction reliability, are essential features to improve performance in a human-robot collaboration in industrial environments.

Augmenting the human hand with robotic extra fingers is a cutting-edge research topic and has many potential applications, in particular as a compensatory and rehabilitation tool for patients with upper limb impairments. Devices composed of two extra fingers are preferred with respect to single finger devices when reliable grasps, resistance to external disturbances, and higher payloads are required. Underactuation and compliance are design choices that can reduce the device complexity and weight, maintaining the adaptability to different grasped objects. When only one motor is adopted to actuate multiple fingers, a differential mechanism is necessary to decouple finger movements and distribute forces. In this paper, the main features of a wearable device composed of two robotic extra fingers are described and analyzed in terms of kinematics, statics, and mechanical resistance. Each finger is composed of modular phalanges and is actuated with a single tendon. Interphalangeal joints include a passive elastic element that allows restoring the initial reference configuration when the tendon is released. The stiffness of each passive element can be customized in the manufacturing process and can be chosen according to a desired closure movement of the fingers. Another key aspect of the device is the differential system connecting the actuator to the fingers.

Grasping and dexterous manipulation remain fundamental challenges in robotics, above all when performed with multifingered robotic hands. Having simulation tools to design and test grasp and manipulation control strategies is paramount to get functional robotic manipulation systems. In this paper, we present a framework for modeling and simulating grasps in the Simulink environment, by connecting SynGrasp, a well established MATLAB toolbox for grasp simulation and analysis, and Simscape Multibody, a Simulink Library allowing the simulation of physical systems. The proposed approach can be used to simulate the grasp dynamics in Simscape, and then analyse the obtained grasps in SynGrasp. The devised functions and blocks can be easily customized to simulate different hands and objects.

The availability of grasp quality measures is fundamental for grasp planning and control, and also to drive designers in the definition and optimization of robotic hands. This work investigates on grasp robustness and quality indexes that can be applied to power grasps with underactuated and compliant hands. When dealing with such types of hands, there is the need of an evaluation method that takes into account the forces that can be actually controlled by the hand, depending on its actuation system. In this paper, we study the potential contact robustness and the potential grasp robustness (PCR, PGR) indexes. They both consider main grasp properties: contact points, friction coefficient, etc., but also hand degrees of freedom and consequently, the directions of controllable contact forces. The PCR comes directly from the classical grasp theory and can be easily evaluated, but often leads to too conservative solutions, particularly when the grasp has many contacts. The PGR is more complex and computationally heavier, but gives a more realistic, even if still conservative, estimation of the overall grasp robustness, also in power grasps. We evaluated the indexes for various simulated grasps, performed with underactuated and compliant hands, and we analyzed their variations with respect to the main grasp parameters.