In this article, the constrained navigation problem for autonomous robots moving in unknown cluttered environments is considered. In particular, it is required to ensure the safety of the path planning and control units during the on-line operations. This statement gives rise to a networked control framework whose the key critical aspects are addressed by resorting to model predictive control technicalities developed within a set-theoretic approach. In particular, a novel control architecture is conceived whose the main features can be summarized as follows: anti-collision capabilities despite time-induced time-delay occurrences along the communication medium; mission accomplishment despite unpredictable obstacle occurrences along the nominal path. These properties are formally proven together with ultimate uniformly boundedness and constraints fulfillment of the regulated trajectory regardless of the vehicle uncertainties. In particular, skid-steered tracked mobile robot are considered for their flexibility and adaptability to operate in arduous scenarios for hazard missions. Final experiments are provided to show the effectiveness and to highlight the main advantages of the proposed control architecture.

This paper presents a set-theoretic time-based trajectory synchronization method to coordinate the skid-steered units subject to slippage phenomena of a multi-robot system. The closed-loop trajectory tracking error dynamics are expressed in the form of an uncertain system subject to external disturbances and actuation constraints. Collision avoidance and coordination are achieved through synchronization of robot trajectories by imposing delays on platform departures. The procedure exploits the trajectory’s feasibility property by solving optimization problems involving Linear Matrix Inequalities (LMIs) constraints. The algorithm operates in separate offline and online phases. In the offline phase, the time delay intervals useful for synchronization are calculated based on the planned feasible trajectories. Then, in the online phase, the actual delay is calculated by solving an optimization problem that minimizes the occupancy time of the shared operational space. The results of several numerical simulations are presented and discussed to demonstrate the proposed solution’s effectiveness.

This work proposes an approach for the fault detection (FD) of a single out-of-water ultrasound range meter for the measurement of sea height. Although they provide high-frequency and accurate measurements, such sensors are prone to faults, and the presence of foam on the water surface can hinder their measurement capabilities. In contrast, underwater pressure sensors provide more reliable but less accurate measurements of wave characteristics. Furthermore, wave attenuation below the sea surface affects the accuracy of pressure sensors-based measurements of wave motion. This work introduces a procedure for performing transfer learning, aimed at leveraging knowledge acquired from pressure sensor data to train a neural network that provides fault detection capabilities in ultrasonic measurement of sea level. The proposed transfer learning procedure takes advantage of linear wave theory, a description of the motion of small amplitude sea waves, to perform domain adaptation. The effectiveness of the proposed approach is discussed through simulations on a real-world dataset in which three common types of faults are injected.

This paper addresses the problem of motion planning for an autonomous, tracked mobile robot whose mathematical model depends on uncertain parameters, with constrained moving capabilities, operating in a cluttered environment. The proposed algorithm exploits the concept of one-step ahead controllable sets. In particular, motion sequences compatible with uncertainties and nonlinear model dynamics are determined in the off-line phase with the aim to determine a collision-free path capable to accomplish the given mission. Conversely, the on-line operations are devoted to determine the most appropriate control action by solving a computationally simple optimization problem. Finally, some preliminary numerical results are instrumental to testify the effectiveness of the proposed approach.

This paper aims to propose a feasible solution to the trajectory planning problem for a constrained skid-steering mobile robot whose control system, sensors and actuators are connected through a communication network. Operating environment is firstly discretized by a finite dimensional grid. Then a weighted graph, whose nodes are the above mentioned points and whose arcs denote the trajectory segments connecting points is defined. Finally an algorithm to obtain the shortest feasible succession of segments connecting given starting and ending points is proposed. Trajectory feasibility is guaranteed in terms of sufficient conditions involving the solution of semi-definite programming (SDP) problems. In order to show the effectiveness of the proposed approach, some numerical simulations are proposed.

Long Term Evolution (LTE) is the emerging 4G wireless technology developed to provide high quality services in mobile environments. It is foreseen that multimedia services and mobile TV will assume an important role for the LTE proliferation in mobile market. However, several issues are still open and meaningful improvements have to be introduced for managing physical resources when group-oriented services should be supplied. To this end, we propose a Frequency Domain Packet Scheduling (FDPS) algorithm for efficient radio resource management of Multimedia Broadcast/Multicast Services (MBMS) in LTE networks. The proposed scheduler exploits an optimization process to organize multicast subscribers in subgroups according to channel quality feedbacks provided by users. Optimization is driven by the aim of minimizing the “user dissatisfaction” with a consequent improvement in the network capacity. The effectiveness of the proposed scheduling algorithm is evaluated through simulation; obtained results demonstrate significant improvement in the multicast traffic performance.