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Pneumatic grippers are hugely employed in robotic applications. Nonetheless, their control is not easy due to difficulty in managing the pressure inside their air chambers. Pneumatic grippers have often simple structure though the lack of affordable control algorithms complicates their usage. Motivated by these reasons, we wish to deliver a new control architecture for the closed-loop control of pneumatic grippers actuated by pressure regulators. The proposed architecture is composed of a main controller resorting to an optimization algorithm and of a state observer that estimates pressures in both gripper chambers, along with the exerted force. Instead, measured quantities (i.e. physical pressure in the gripper chambers and force recorded by a load cell between the gripper fingers) are used as inputs for the state observer to improve its output. The pneumatic gripper performance benefits from the joint action of the controller and of the state observer, as experimentally demonstrated. The gripper response will be shown for different types of inputs and on different setups.

This chapter has shown the feasibility of a tendon driven robot eye featuring the implementation of Listing's Law on a mechanical basis. The design of the robot is based on a model which is strongly inspired on assumptions derived from physiological evidence. The achievements discussed in this chapter represent the starting point for the development of a more complex humanoid robot eye. From the mechanical point of view the most important advancement is represented by the possibility of extending the actuation to six tendons in order to enable the implementation of more complex ocular motions as the vestibulo-ocular reflex. From a theoretical point of view a more complete analysis of the properties of the proposed eye model could provide further understanding of the dynamics of saccadic motions. Furthermore, other issues such as eye miniaturization and embedding of image processing algorithms modules for direct visual feedback represent important challenges for the development of fully operational devices.

Hand-eye calibration of laser profile sensors is the process of extracting the homogeneous transformation between the laser profile sensor frame and the end-effector frame of a robot in order to express the data extracted by the sensor in the robot's global coordinate system. For laser profile scanners this is a challenging procedure, as they provide data only in two dimensions and state-of-the-art calibration procedures require the use of specialised calibration targets. This paper presents a novel method to extract the translation-part of the hand-eye calibration matrix with rotation-part known a priori in a target-agnostic way. Our methodology is applicable to any 2D image or 3D object as a calibration target and can also be performed in situ in the final application. The method is experimentally validated on a real robot-sensor setup with 2D and 3D targets., The first two authors contributed equally to this work. Accepted to the IEEE International Conference on Robotics and Automation (ICRA) 2021

Mechanical systems are typically composed of a number of contacting surfaces that move against each other. Such surfaces are subject to friction forces. These dissipate part of the actuation energy and cause an undesired effect on the overall system functioning. Therefore, a suitable model of friction is needed to elide its action. The choice of such a model is not always straightforward, as it is influenced by the system properties and dynamics. In this paper, we show the identification of different friction models and evaluate their prediction capability on an experimental dataset. Despite being state-of-the-art models, some modifications were introduced to improve their performance. A pneumatic gripper was used to collect the data for the models evaluation. Two experimental setups were mounted to execute the experiments: information from two pressure sensors, a load cell and a position sensor was employed for the identification. During the experiments, the gripper was actuated at different constant velocities. Results indicate that all the identified models offer a proper prediction of the real friction force.

The paper introduce a robotics software control architecture suitable for the development of complete robotic industrial applications. The architecture fuse the state-of-the-art software technologies in a single standalone platform to provide an easy integration between all the software components necessary to control a robotic application, i.e. PLC logic, robot motion program. The main goal is to provide an architecture as much as possible hardware agnostic to develop easily portable software.

Wearable sensors are gaining in popularity because they enable outdoor experimental monitoring. This paper presents a cost-effective sensorised insole based on a mesh of tactile capacitive sensors. Each sensor's spatial resolution is about 4 taxels/cm^2 in order to have an accurate reconstruction of the contact pressure distribution. As a consequence, the insole provides information such as contact forces, moments, and center of pressure. To retrieve this information, a calibration technique that fuses measurements from a vacuum chamber and shoes equipped with force/torque sensors is proposed. The validation analysis shows that the best performance achieved a root mean square error (RMSE) of about 7 N for the contact forces and 2 N m for the contact moments when using the force/torque shoe data as ground truth. Thus, the insole may be an alternative to force/torque sensors for certain applications, with a considerably more cost-effective and less invasive hardware., 21 pages, 12 figures

In this study, a textile-based wearable strain sensor is fabricated to monitor human muscular activities with high sensitivity and large working range. To achieve electrical conductivity, a gum-like sticky polyvinyl acetate-co-vinyl laurate polymer (commercial name: VINNAPASS) is mixed with 50 wt % of carbon nanofiber (CNFs) using ethyl acetate as co-solvent. The VINNAPASS/CNFs-based ink is spray coated onto a stretchable polyethylene terephthalate fabric (commercial name: Lycra) and subsequently covered and stabilized with polydimethylsiloxane protective layer. Another reference sensor is also prepared using thermoplastic polyurethane (TPU) with equal concentration of CNFs. The strain sensor made with VINNAPASS demonstrated sheet resistance, maximum elongation at break, gauge factor (GF) and working range of 32.27 ± 1.60 Ω/□, 230 ± 6%, 67.12, >170% as compared to 48.44 ± 2.33 Ω/□, 122 ± 7%, 39.97 and ~100% for the sensor made with TPU, respectively. Moreover, the VINAPASS-based strain sensor displayed complete self-healing and >90% reversible electrical properties on damage, while the TPU-based sensor was not healable. Finally, the VINNAPASS-based sensor is used to monitor folding-unfolding of human finger and wrist as well as bicep muscle contraction and relaxation, and is envisioned for monitoring human muscular motions during physical activities and exercising.

This paper outlines the design of the hand of the R1 humanoid robot. The hand uses a completely plastic structure with embedded electronics. It has 2 actuated degrees of freedom (DOF) with 4 phalanges, coupling two phalanges to each degree of actuation. A novel series elastic module was developed within the hand. It is used in force sensing and protects the hand from impact loads. The series elastic module is designed, characterized and evaluated across the working range of the hand. The hand also has position sensors at all joints and tactile sensors for tactile feedback on its phalanges. The hand is completely self-contained with all control boards and motors housed within the structure. It is then tested and evaluated against user needs.

In recent years the robotics field has witnessed an interesting new trend. Several companies started the production of service robots whose aim is to cooperate with humans. The robots developed so far are either rather expensive or unsuitable for manipulation tasks. This article presents the result of a project which wishes to demonstrate the feasibility of an affordable humanoid robot. R1 is able to navigate, and interact with the environment (grasping and carrying objects, operating switches, opening doors etc). The robot is also equipped with a speaker, microphones and it mounts a display in the head to support interaction using natural channels like speech or (simulated) eye movements. The final cost of the robot is expected to range around that of a family car, possibly, when produced in large quantities, even significantly lower. This goal was tackled along three synergistic directions: use of polymeric materials, light-weight design and implementation of novel actuation solutions. These lines, as well as the robot with its main features, are described hereafter.