Search Results (8)

Underwater dynamic target detection, classification, localization, and tracking (DCLT) is central to maritime surveillance and monitoring and increasingly relies on distributed AUV-based robotic sonar networks operating in passive listening and, when required, cooperative multistatic modes. Achieving a robust performance in realistic oceans remains challenging, because sensor placement must adapt to time-varying acoustic conditions and target priors while preserving acoustic communication connectivity, and because frequent reconfiguration under dynamic currents makes classical large-scale planning computationally expensive. This paper presents an integrated deep reinforcement learning (DRL)-based framework for passive-stage sonar placement and dynamic reconfiguration in distributed AUV networks. First, we cast placement as a constructive finite-horizon Markov decision process (MDP) and train a Proximal Policy Optimization (PPO) agent to sequentially build a collision-free layout on a discretized surveillance grid. The terminal reward is formulated to jointly optimize the environment-aware detection performance, computed from BELLHOP-based transmission loss models, and global network connectivity, quantified using algebraic connectivity. Second, to enable time-critical reconfiguration, we estimate flow-aware motion costs for all AUV–destination pairs using a PPO with a Long Short-Term Memory (LSTM) trajectory policy trained for partial observability. The learned policy can be deployed onboard, allowing each AUV to refine its path online using locally sensed currents, improving robustness to ocean-model uncertainty. The resulting cost matrix is solved via an efficient zero-element assignment method to obtain the optimal one-to-one reassignment. In the reported simulation studies, the proposed Sequential PPO placement method achieves a final reward 16–21% higher than Particle Swarm Optimization (PSO) and 2–3.7% higher than the Genetic Algorithm (GA), while the proposed PPO + LSTM planner reduces average travel time by 30.44% compared with A*. The proposed closed-loop architecture supports frequent re-optimization, scalable fleet operation, and a seamless transition to communication-supported cooperative multistatic tracking after detection, enabling efficient, adaptive DCLT in dynamic marine environments. Full article

In this paper, a connecting joint capable of underwater autonomous docking and separation is proposed, which can be used for a reconfigurable articulated underwater robot (RAU robot). The structural design, optimization, and experimental validation of the connecting joint are presented in detail. First, the concept of the RAU robot is introduced, along with its different operational modes and the application scenarios. Second, the specific structural design and basic functions of the connecting joint are described. Third, a dynamic model of the docking process between different vehicles is established and simulated by kinematic simulation software. Through discretely sampling the parameter space, the optimal parameter combination is obtained. Finally, a prototype of the connecting joint is fabricated and functional tests are conducted. The impact forces on the docking rods before and after optimization are compared. The results show that the designed connecting joint can fulfill the functional requirements for autonomous docking of the underwater robot, and the maximum impact force is reduced by 27.08% compared to the one before optimization. Full article

Multi-agent coverage control plays a crucial role in the modeling and coordination of complex systems, especially for teams of robots that, through frequent interactions with each other and their environment, can accomplish complex tasks in a distributed and parallel manner. However, most existing studies on coverage control for multi-agent systems are limited to two-dimensional environments, with few addressing the height factor critical to three-dimensional spaces. This study proposes a novel approach that adapts centroidal Voronoi tessellation (CVT) with a time-varying density function and Control Barrier Functions (CBFs) for dynamic coverage in 3D environments. By reconfiguring these methodologies, this approach enhances distribution and coordination efficiency within 3D spaces while ensuring safe, collision-free navigation. The simulation results validate the effectiveness of the proposed approach, demonstrating its potential for the efficient deployment of multi-robot systems, such as unmanned autonomous vehicles and unmanned autonomous underwater vehicles, in diverse operational contexts. Full article

This paper proposes a hybrid propulsion-based small underwater robot for robust trajectory tracking control in a harsh and complex underwater environment. The robot is equipped with a Coanda-effect jet thruster and a pair of propeller-based reconfigurable magnetic-coupling thrusters, allowing it to traverse safely in confined or cluttered spaces as well as cruise efficiently in the open water. To investigate the robot dynamic modeling, we first formulated its simplified mathematical model and estimated the hydrodynamic coefficients by performing the planar motion mechanism using CFD (computational fluid dynamics) simulation. Then, a double-loop trajectory tracking control architecture was designed considering the model uncertainties and environmental disturbances. Based on Lyapunov theory, the outer-loop kinematic control produces the virtual velocity command, while the inner-loop dynamic control adopts the full-state feedback L1-adaptive control to match the command. The asymptotic convergence of the tracking errors and the stability of the whole closed-loop system are guaranteed. Finally, comparative simulations in the presence of unknown disturbances and the variation of model parameters were carried out to verify the robustness of our proposed trajectory tracking control, which is also suitable for the separated son robots. Full article

A dynamically reconfigurable underwater robot, which can vary its configuration during a mission, would be useful for confined environment exploration and docking because of its versatility. A mission can be performed by choosing among different configurations, and the energy cost may increase, owing to the reconfigurability of the robot. Energy saving is the critical issue in long-range missions with underwater robots. Moreover, control allocation must be considered for a redundant system and input constraints. We propose an approach for an energy-efficient configuration and control allocation for a dynamically reconfigurable underwater robot that is built for karst exploration. The proposed method is based on sequential quadratic programming, which minimizes an energy-like criterion with respect to robotic constraints, i.e., mechanical limitations, actuator saturations, and a dead zone. The optimization problem is solved in each sampling instant. Two popular tasks for underwater robots, i.e., path-following and station-keeping (observation) problems, are simulated, and the simulation results show the efficiency of the method. Moreover, an experiment is carried out to highlight the results. Full article

This paper presents the design and experiment of an autonomous underwater robot which can change the geometric configuration of its actuators, according to mission requirements or environmental constraints. The robot consists of two subsystems: forward part with three thrusters and backward part with four thrusters. The position and orientation of these thrusters can be dynamically changed during missions. Being different from most of other reconfigurable underwater robots which were designed as linked-modules, our robot has a unified design. It is suitable for specific mission in confined environments (e.g., karst exploration) in which the robot has to modify its shape to go through a narrow section or align the most part of its thrusters in the direction of a strong current, for examples. The design procedure, from hardware to software, of the robot is presented and experimental results are shown to demonstrate the versatility of the robot. Furthermore, the discussion and comparison between our robot and other underwater robots with adaptable actuation geometry are presented to highlight advantages of our design. Finally, the idea of using our robot for classic docking problem, which has some common features with karst exploration requirements in using dynamically reconfigurable robots, is discussed. Full article

Since the development of the first autonomous underwater vehicles, the demanded tasks for subsea operations have become more and more challenging as, for instance, intervention, maintenance and repair of seabed installations, in addition to surveys. As a result, the development of autonomous underwater reconfigurable vehicles (AURVs) with the capability of interacting with the surrounding environment and autonomously changing the configuration, according to the task at hand, can represent a real breakthrough in underwater system technologies. Driven by these considerations, an innovative AURV has been designed by the Department of Industrial Engineering of the University of Florence (named as UNIFI DIEF AURV), capable of efficiently reconfiguring its shape according to the task at hand. In particular, the UNIFI DIEF AURV has been provided with two extreme configurations: a slender (“survey”) configuration for long navigation tasks, and a stocky (“hovering”) configuration designed for challenging goals as intervention operations. In order to observe the several dynamic features for the two different configurations, a novel formulation for the dynamic maneuverability analysis (DMA) of an AURV, adapting Yoshikawa’s well-known manipulability theory for robotic arms, is proposed in this work. More specifically, we introduce a novel analysis which relates the vehicle body-fixed accelerations with the rotational speed of each thruster, taking into account also the AURV dynamic model for each configuration and the propulsion system. Full article

The concept of reconfigurable magnetic coupling thrusters (RMCT) applied to the vectorial thrust of autonomous underwater vehicles (AUV) has been recently developed and presented. This technology ensures greater robot watertightness with enhanced maneuvering capabilities, which are desired features in agile AUVs for marine renewable energy (MRE) system maintenance. It is possible since in RMCTs the driving torque is magnetically transmitted to the propeller, which has its orientation changed. This work is focused on the coupling and control torque calculation and further analysis of the latest prototype version (Flat-RMCT), in the static condition for the full thrust vector range. For this purpose, a numerical model is implemented and validated with experimental results. The numerical model is based on the finite volume integral method. The results indicate that the minimum magnetic reluctance propensity creates not only the expected magnetic spring effect but also an auto-driving torque due to the non-axial symmetry of coupling rotors, which exists only for reconfigurable couplings. Mathematical functions are proposed to model these effects and they are used to extend the understanding of the coupling. These models can be used to compose a full and accurate dynamic model for a better RMCT simulation, identification, and control. Full article