The use of drones in agriculture is becoming more and more popular. The paper presents a novel approach to distinguish 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 depths.

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.

The present paper introduces a novel type of haptic interface which is fully portable and employs only onboard sensors and electronics to solve accurate localization and force feedback generation. The device offers 2DOF force control while sliding on a plane and maintaining its orientation comfortable for the user. The device generates force feedback information without any intermediate link between the motion wheels and the grasping handle. The device has been designed for application in neuro-rehabilitation protocols and it adopts specific mechanical, electrical and control solutions in order to cope with patient requirements. The paper describes the mechanical and electronic solutions as well as the most relevant features of control implementation issues that were addressed in the system design.

Any teleoperation system involving two distant devices is affected by communication delay due to the physical gap between the devices. Several approaches based on wave variables have already been proposed to deal with time-varying delay. However, these approaches are too conservative resulting in high degradation from the constant time delay case. In this paper, we propose a new control scheme for bilateral teleoperation under time-varying communication delay entirely developed in the wave variables domain. The proposed method minimizes the performance degradation from the constant time delay case. Experimental results show the validity of the proposed scheme.

Nowadays, multirotors are versatile systems that can be employed in several scenarios, where their increasing autonomy allows them to achieve complex missions without human intervention. This paper presents a framework for autonomous missions with low-cost Unmanned Aerial Vehicles (UAVs) in Global Navigation Satellite System-denied (GNSS-denied) environments. This paper presents hardware choices and software modules for localization, perception, global planning, local re-planning for obstacle avoidance, and a state machine to dictate the overall mission sequence. The entire software stack has been designed exploiting the Robot Operating System (ROS) middleware and has been extensively validated in both simulation and real environment tests. The proposed solution can run both in simulation and in real-world scenarios without modification thanks to a small sim-to-real gap with PX4 software-in-the-loop functionality. The overall system has competed successfully in the Leonardo Drone Contest, an annual competition between Italian Universities with a focus on low-level, resilient, and fully autonomous tasks for vision-based UAVs, proving the robustness of the entire system design.

Drone technology is advancing rapidly and represents significant benefits during firefighting operations. This paper presents a novel approach for autonomous firefighting missions for Unmanned Aerial Vehicles (UAVs). The proposed UAV framework consists of a local planner module that finds an obstacle-free path to guide the vehicle toward a target zone. After detecting the target point, the UAV plans an optimal trajectory to perform a precision ballistic launch of an extinguishing ball, exploiting its kinematics. The generated trajectory minimises the overall traversal time and the final state error while respecting UAV dynamic limits. The performance of the proposed system is evaluated both in simulations and real tests with randomly positioned obstacles and target locations. The proposed framework has been employed in the 2022 UAV Competition of the International Conference on Unmanned Aircraft Systems (ICUAS), where it successfully completed the mission in several runs of increasing difficulty, both in simulation and in real scenarios, achieving third place overall. A video attachment to this paper is available on the website https://www.youtube.com/watch?v=_hdxX2xXkVQ.