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The PlaCE project aims at investigating technologies and solutions for the ecosustainable reuse of offshore platforms at the end of their production phase. In this context, robotic mobile solutions that allow in a versatile way to monitor the activities by acquiring environmental data and parameters in the entire area of interest have been explored. This paper presents a solution achieved through the development of the proof-of-concept of a robotic technology concerning a hybrid Autonomous / Remotely Piloted Aircraft System (A/RPAS), hereinafter referred to as Amphibious Drone, operating in complete autonomy and having the platform as an operational base. The Amphibious Drone is developed to cover the entire area of interest surrounding the platform being converted, with the ability to carry the measuring instruments and probes in aerial overflight for monitoring the sea surface and the surface structures as well as ditching to deploy a sensors-equipped probe for measuring underwater parameters along the water column. A wide range of probes and instruments have been integrated into the system such as multispectral camera, Photosynthetically Active Radiation (PAR) probes, Conductivity-Temperature-Depth (CTD) probes, etc. for the analysis of oceanographic and biological parameters of the marine ecosystem. The management of the Amphibious Drone, as regards the shelter between missions, battery recharging, data exchange, required reconfigurations and missions scheduling is carried out from a specially designed Docking Station. The PlaCE project is co-funded by the European Union within the projects “PON Ricerca e Innovazione 2014-2020”.

Quadruped robots have garnered significant attention in recent years due to their ability to navigate through challenging terrains. Among the various environments, agriculture fields are particularly difficult for legged robots, given the variability of soil types and conditions. To address this issue, this study proposes a novel navigation strategy that utilizes ground reaction forces to calculate online artificial potential fields, which are then applied to the robot’s feet to avoid low-traversability regions. The strategy also incorporates the net vector of the attractive potential field towards the goal and the repulsive field to avoid slippery regions, which dynamically adjusts the quadruped’s gait. A realistic simulation environment validates the proposed navigation framework with case studies on randomly generated terrains. A comprehensive comparison with baseline navigation methods is conducted to assess the effectiveness of the proposed approach.

Energy grids represent a fundamental infrastructure of any country. These structures consist of many kilometres of power lines that must be periodically inspected and maintained. Among the necessary operations are installing and removing bird diverters to reduce bird strikes on power lines. These devices are intended to improve birds’ detection of power lines and reduce the risk of collision. Often, the installation and removal of bird diverters from power lines is accomplished by humans operating from helicopters or directly on the power lines. Apart from the considerable cost of these operations, working in elevated environments creates human safety risks. To reduce these risks, this paper proposes a novel solution to automatize these tasks. The proposed solution is a prototype gripper that can be mounted on unmanned aerial vehicles (UAVs) and remotely operated to install or remove bird diverters. This work presents a mechatronic device and software architecture system that is experimentally evaluated in a laboratory mock-up, which consists of a manipulator equipped with the proposed tool for removing a bird diverter. Future work is needed to deploy the proposed tool on a UAV.

This paper presents a robust control strategy for controlling the flight of an unmanned aerial vehicle (UAV) with a passively (fixed) tilted hexarotor. The proposed controller is based on a robust extended-state observer to estimate and reject internal dynamics and external disturbances at runtime. Both the stability and convergence of the observer are proved using Lyapunov-based perturbation theory and an ultimate bound approach. Such a controller is implemented within a highly realistic simulation environment that includes physics motors, showing an almost identical behavior to that of a real UAV. The controller was tested for flying under normal conditions and in the presence of different types of disturbances, showing successful results. Furthermore, the proposed control system was compared with another robust control approach, and it presented a better performance regarding the attenuation of the error signals.

The significant advances in last decade in the research and technology of multi-rotor design, modeling and control, supported by the increasing variety of commercially available platforms, components and manufacturers, have facilitated a rise in the novel applications of aerial robots, capable of not only perceiving, but also interacting with the environment, allowing the realization of diverse operations and tasks in areas and workspaces that are difficult to access by human operators or ground vehicles [...]

The power grid is an essential infrastructure in any country, comprising thousands of kilometers of power lines that require periodic inspection and maintenance, carried out nowadays by human operators in risky conditions. To increase safety and reduce time and cost with respect to conventional solutions involving manned helicopters and heavy vehicles, the AERIAL-CORE project proposes the development of aerial robots capable of performing aerial manipulation operations to assist human operators in power lines inspection and maintenance, allowing the installation of devices, such as bird flight diverters or electrical spacers, and the fast delivery and retrieval of tools. This manuscript describes the goals and functionalities to be developed for safe local aerial manipulation, presenting the preliminary designs and experimental results obtained in the first year of the project.

With the advances in networking technologies, robots can use the almost unlimited resources of large data centers, overcoming the severe limitations imposed by onboard resources: this is the vision of Cloud Robotics. In this context, we present DewROS, a framework based on the Robot Operating System (ROS) which embodies the three-layer, Dew-Robotics architecture, where computation and storage can be distributed among the robot, the network devices close to it, and the Cloud. After presenting the design and implementation of DewROS, we show its application in a real use-case called SHERPA, which foresees a mixed ground and aerial robotic platform for search and rescue in an alpine environment. We used DewROS to analyze the video acquired by the drones in the Cloud and quickly spot signs of human beings in danger. We perform a wide experimental evaluation using different network technologies and Cloud services from Google and Amazon. We evaluated the impact of several variables on the performance of the system. Our results show that, for example, the video length has a minimal impact on the response time with respect to the video size. In addition, we show that the response time depends on the Round Trip Time (RTT) of the network connection when the video is already loaded into the Cloud provider side. Finally, we present a model of the annotation time that considers the RTT of the connection used to reach the Cloud, discussing results and insights into how to improve current Cloud Robotics applications.