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Underwater monitoring activities are crucial for the preservation of marine ecosystems. Currently, scuba divers are involved in data collection campaigns that are repetitive, dangerous, and expensive. This article describes the application of Information Communication Technology (ICT) tools to underwater visual data for monitoring purposes. The data refer to a Posidonia Oceanica survey mission carried out by a scuba diver using a Smart Dive Scooter equipped with visual acquisition and acoustic localization systems. An acoustic-based strategy for geo-referencing of the optical dataset is reported. It exploits the synchronization between the audio track extracted from a camera and the transponder pings adopted for the acoustic positioning. The positioning measurements are employed within an extended Kalman filter to estimate the diver's path during the mission. A visual odometry algorithm is implemented within the filter to refine the navigation state estimation of the diver with respect to the acoustic positioning only. Moreover, a smoothing step based on the Rauch-Tung-Striebel smoother is applied to further improve the estimated diver's positions. Finally, the article reports the results of two different data processing for monitoring applications. The first one is an image mosaicking obtained by concatenating subsequent frames, whereas the second one refers to a qualitative distribution of the Posidonia Oceanica over the mission area accomplished through an image segmentation process. The two outcomes are plotted over a satellite image of the surveyed area, showing that the proposed process is an effective tool capable of facilitating divers in their monitoring and inspection activities.

This paper describes the process of design, analysis, and scoring with both subjective and objective criteria, of a set of possible haptic inceptors configurations to be used as primary flight control devices for a class of future tilt rotor vehicles. Several scoring criteria were adopted like ergonomics, cognitive compatibility, easiness of recovery in fault situations, and expected workload among several others. Each criterion was weighted to obtain a scoring matrix for a total of 18 different configurations, some "classic", some novel, leading to an overall ranking. The matrix was used to select the best candidate configurations to be tested using a human-in-the-loop simulator in the context of the EU Funded CleanSky2 SMARTeR Project. After a final review phase, the best solution will be adopted to actually fly the Leonardo NextGen Civil Tilt Rotor Technological Demonstrator in the context of the EU Funded CleanSky2 SAIS Project.

The collaboration between humans and robots represents a major topic in robotics. In the underwater domain, the employment of unmanned robots could help divers perform number of tasks such as monitoring and inspection activities. However, the underwater environment poses severe limitations that still need to be overcome to achieve autonomous operations. This research work represents an intermediate step in the human-robot switchover in underwater domain for a particular application and involves the use of ICT tools to facilitate human divers in the monitoring of Posidonia Oceanica (Po) meadows. The paper reports a strategy to geo-reference underwater visual data exploiting the synchronization between the audio track recorded by a camera and the transponder pings adopted for the acoustic positioning system. The paper also reports the exploitation of the geo-referenced data for the identification of Po meadow over the mission area using a Machine Learning algorithm. The results are very promising and can lead to an accurate geo-referenced identification of Po and the reconstruction of the surveyed area., https://youtu.be/0k8tb9AqiGo

The paper presents an overview and the main results of the Erasmus+ project titled Interactive Course for Control Theory – ICCT. The project was started by four European Universities when they identified by a survey that students find Control Theory more challenging to understand compared to other subjects. The project's main goal was to develop a platform, which would offer examples from the field of Control Theory in an interactive way – ICCT. Frequently asked questions (FAQ) and test exam questions were added as well. To support the course, an accompanying textbook was prepared. At this point, the course and the accompanying textbook are available in English and the languages of the partner universities ; since both of them are publicly available, we assume they will be offered in other languages in future. The benefits of implementing our interactive course are already visible in better survey results and improved grades in Control Theory-related subjects.

Energy saving is a relevant issue for battery powered Intervention Autonomous Underwater Vehicles which are designed for both short and long-range mission. The energy consumption of an I-AUV is affected by several effects like hydrodynamics, onboard electronics and thrusters cross-couplings. I-AUVs are usually over-actuated system, thus the actuator's interaction takes relevance and should take part within the energy saving process. In this paper the authors present a study on optimal control allocation that aims at considering the interactions between the propellers of an over actuated vehicle where usually two or more thrusters can interfere each other resulting in reduction of the allocation efficiency. The paper presents the mathematical formulation for interacting propeller considering the wake effect and proposes to dynamically adjust the control allocation matrix in order to obtain a cost effective control allocation without modifying the control layer. The existence of a minimum in the energy consumption during the cruising task in function of the parametric control allocation matrix is proved numerically. Thus a perturbation-based extremum seeking approach is used in order to dynamically adapt the parametric allocation matrix and seek the optimal allocation setpoint without explicit knowledge of the real coupling.

Control of a helicopter is a highly demanding task for the human operator, due to its unstable and coupled dynamics. Indeed, the pilot is required to constantly give inputs on the control device that are necessary to both move the vehicle towards a specific direction and, at the same time, to stabilize the system dynamics. Haptic support systems may be used as an alternative solution to help pilots in such demanding task. Design of an effective haptic system requires knowledge of the target trajectory. However, in many realistic scenarios, the target trajectory is not known in advance. For instance, in a helicopter free-flight task the pilot is free to choose any possible maneuver at any time, and the pilot intended trajectory cannot be known a priori. To provide the pilot with a haptic feedback that helps him/her to accomplish the intended maneuver, estimation of pilot intended trajectory is crucial. In this paper, a neural network approach is proposed to infer pilot intent based on data collected from maneuvers performed by an expert helicopter pilot, in a 2-DoF lateral/longitudinal scenario. Successively, a haptic feedback is designed to help the pilots to accomplish the intended trajectories. The proposed shared control system is evaluated in a human-in-the-loop experiment with minimally-trained participants in a fixed-base simulator. The participants performed a flight control task which included diagonal, lateral and longitudinal motions. Each participant performed the maneuver in two different conditions: with and without haptic feedback. Results showed effectiveness of the haptic feedback on participants performance compared to manual control.

The European brown hare (Lepus europaeus) is an important game species throughout Europe. In Italy, for preventing the introduction of allochthonous strains, the management of brown hare populations has focused on the establishment of small protected areas (ZRCs), appositely managed for disposing of wild-born hares for restocking hunting territories. We investigated the effects of both land cover and surveillance on hare density and habitat preferences in 20 ZRCs, monitored twice per year (pre- and post-breeding periods) between 1997 and 2017. Density, as assessed by spotlight counts, ranged between 2.8 and 47.0 ind/km2 in spring and 5.0 and 68.4 ind/km2 in autumn. Surveillance, percent length of protected boundaries, year of institution and habitat diversity, as assessed by Shannon’s Index, were the main factors affecting hare density. During their foraging activity, hares selected ryegrass, hayfields and lucerne, while avoided maize stubble and ploughed fields and were never recorded in poplar plantations or next to human settlements. While the effects of habitat heterogeneity on hare density have been widely studied, we suggest that the involvement of local stakeholders may be of paramount importance for ensuring effective conservation measures.

Haptic support systems have been widely used for supporting human operators when performing a manual control task. These systems are commonly designed to track known target trajectories. However, the trajectory to track is not known in many realistic cases. For instance, the pilot-intended trajectory is not known beforehand when considering a helicopter pilot flying in free-flight. This paper proposes a possible approach to design a haptic shared control system when the target trajectory is not known a priori. Especially, the aim of the proposed design is to help minimally trained pilots during a 2-degree-of-freedom lateral/longitudinal helicopter free-flight task. To accomplish this goal, first, a Pilot Intent Estimator (PIE) is developed to infer pilot intent. Then, the corresponding intended trajectory is generated. Finally, a haptic feedback is designed to track the estimated intended trajectory. The designed PIE was evaluated in a preliminary test with an experienced helicopter pilot. Then, a human-in-the-loop experiment with minimally trained participants was conducted to assess the proposed shared control system. Results showed the effectiveness of the PIE to estimate the correct direction of motion chosen by the pilot. Furthermore, the haptic feedback helped participants to accomplish the control task with better task performance (i.e., lower tracking errors and lower amount of control activity) compared with manual control.

This chapter describes the main challenges, and the corresponding solutions, encountered during the development of the guidance, navigation, and control (GNC) systems for the autonomous underwater vehicles (AUVs) and the autonomous surface vehicles (ASVs) involved in the Widely scalable Mobile Underwater Sonar Technology (WiMUST) project.