The use of drones in agriculture is becoming more and more popular. The paper presents a novel approach to dis- tinguish between different field’s plowing techniques by means of an RGB-D sensor. The presented system can be easily integrated in commercially available Unmanned Aerial Vehicles (UAVs). In order to successfully classify the plowing techniques, two different measurement algorithms have been developed. Experimental tests show that the proposed methodology is able to provide a good classification of the field’s plowing depth

The present work, which describes the mechatronic design and development of a novel rehabilitation robotic exoskeleton hand, aims to present a solution for neuromusculoskeletal rehabilitation. It presents a full range of motion for all hand phalanges and was specifically designed to carry out position and force-position control for passive and active rehabilitation routines. System integration and preliminary clinical tests are also presented.

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Working machines in construction sites or emergency scenarios can operate in situations that can be dangerous to an operator both\ud for direct control of the machine or teleoperation in co-presence. Remote operation has been typically hindered by limited sense\ud of presence of the operator in the remote of the environment to due the reduced field of view of cameras. Starting from these\ud considerations we are introducing a novel real-time panoramic telepresence system for construction machines. This system does\ud allow fully immersive operations in critical scenarios while keeping the operator in a safe location at moderate distance from the\ud construction site. An omnidirectional stereo vision head mounted over the machine acquires and streams data to the operator with a\ud streaming technique that focuses on the current direction of site of the operator. According to the motion of the operators head, the\ud telepresence system will determine the involved cameras to use and the appropriate region of interest in cameras. The operator uses\ud a head-mounted display to experience the remote site also with the possibility to view digital information overlaid to the remote\ud scene as a type of augmented reality. The paper addresses the design and architecture of the system starting from the vision system\ud and then proceeding to the immersive visualizatio

The Fourth Industrial Revolution, or Industry 4.0, aims at automating traditional manufacturing and industrial practices using modern smart technology. Autonomous mobile robots equipped with different sensors and employing different techniques have been proposed in the literature in the logistics and inventory warehouse management contexts. Efficient robot motion and planning depend on precise localization, mapping, and awareness of the environment. To properly localize items, recent attempts have been made employing radio frequency identification (RFID) in a 3D environment. This manuscript introduces four least mean squares methods to estimate the 3D positions of tags employing synthetic apertures and phase unwrapping. The proposed methods approach the localization problem solving a system of equations typical of multilateration methods to find the intersections of multiple hyperboloids. The novelty introduced here is the use of unwrapped phase distances to compute pseudo ranges for the multilateration problem. The use of such a technique is feasible thanks to precise mobile robot localization and custom navigation policies. All the analyzed methods are suitable for online localization due to reduced computation timings and have been tested on three different datasets. Two of them contain virtual data that has been generated by simulation, while the other one comes from an indoor experimental setup. Simulated tests show that combined antenna motions in 3D space (including Z-axis) improve the localization obtaining errors under the centimeter for 3D localization. Experimental tests obtained results as low as 13 cm of mean accuracy for 3D localization and 0.21 cm for 2D localization.

This work addresses the problem of semi-automatic inspection and navigation in confined environments. A system that overcomes many challenges at the state of the art is presented. It comprises a multirotor able to inspect an industrial combustion chamber thus working in a GPS-denied environment with poor lighting conditions, in the presence of magnetic and communication disturbances, iron dust and repetitive patterns on the structure walls. The presented system is able to pass through narrow entrances but still capable of acquiring high resolution images and to allow operators to perform inspection of the structures. Starting from the captured data, the system is able to provide a 3D reconstruction of the inspected environment for offline analysis.