Journals
2026 EN
Ren Junxing · Xing Liudong · Lin YiKuei
ABSTRACT Unmanned aerial vehicles (UAVs) are revolutionizing a wide range of military and civilian applications. Since mission failures caused by malfunctions of UAVs can incur significant economic losses, modeling and ensuring the reliability of UAV‐based mission systems is a crucial area of research with challenges posed by multiple dependent phases of operations and collaborations among heterogeneous UAVs. The existing reliability models are mostly applicable to single‐UAV or homogeneous multi‐UAV systems. This paper advances the state of the art by proposing a new analytical modeling method to assess the reliability of a multi‐phased mission performed by heterogeneous collaborative UAVs. The proposed method systematically integrates an integral‐based Markov approach with a binary decision diagram‐based combinatorial method, addressing inter‐ and intraphase collaborations as well as phase‐dependent configurations of heterogeneous UAVs for accomplishing different tasks. As demonstrated by a detailed analysis of a two‐phase rescue mission performed by six UAVs, the proposed method has no limitations on UAV's time‐to‐failure and time‐to‐detection distributions. Another contribution is to formulate and solve UAV allocation problems, achieving a balance between mission success probability and total cost. Given the uncertainties inherent in the mission scenario, the random phase duration problem is also examined.
Journals
2026 EN
Zhang Yang · Zhang Min · Wei Keke
+3 more
ABSTRACT In modern industrial systems, the outsourcing of the maintenance service of mission‐critical equipment (MCE) is becoming common practice for increasing the system flexibility and decreasing operating costs. For the MCE operator and the service provider, a performance‐based contract (PBC) is critical to the cooperation between these two parties. In the PBC of maintenance service, equipment availability is often used as the performance indicator. Considering the potential loss due to the MCE downtime, business interruption (BI) insurance is often purchased by the practitioners for mitigating the operating risks. This paper designs a PBC by taking the supplier's risk attitudes and BI insurance into account. Specifically, this paper constructs a PBC design model using principal‐agent analysis and explores the role of BI insurance in contract parameters (the fixed payment and the penalty/reward rate). Results show that greater (smaller) fixed payments and penalties in PBCs are more incentive for suppliers as their risk‐averse (risk‐seeking) degree rises. When BI insurance is purchased, the operator would be more suitable to use a contract with smaller penalties (for risk‐averse, risk‐neutral, risk‐seeking suppliers) compared to a PBC without BI insurance. Finally, a numerical example illustrates our proposed PBC model.
Journals
2026 EN
Arriaza Antonio · Navarro Jorge · OrtegaJiménez Patricia
ABSTRACT This article assesses risk times in mission‐oriented systems with high safety standards. We examine critical times under two safety policies. The first requires that the system's reliability function, known the first failure of the components, must exceed a reliability level throughout the mission. The second demands that the conditional distribution of the system's lifetime, given the first failure of the components, must be more reliable, in terms of the usual stochastic order, than the original system's lifetime. Our study analyzes the critical times at which both policies remain viable. Our methodology, applicable to multiple failure scenarios, identifies sufficient conditions for the existence of these times. We offer explicit solutions for parallel systems with IID components and a general method for dependent and identically distributed components. The study includes practical examples and introduces a non‐parametric estimator for the critical times.
Journals
2026 EN
Yang Kaiqi · Wang Xiaoli · Yang Hengyu
+1 more
ABSTRACT This paper presents a team‐based coverage strategy for deploying heterogeneous agents in corridor‐type regions. Initially, the corridor‐type region is divided into team‐level coverage areas using a Voronoi diagram, which is further subdivided among team members using a power diagram. The coverage region, characterized by dynamic boundaries, moves within the mission area. A gradient descent‐based control law is designed for each agent, which incorporates the dynamic boundary caused by the movement of the leading agents and the size change of power cells. The proposed control laws ensure that the agents converge to a locally optimal coverage configuration, with a balanced workload distribution. Additionally, a team‐based formation control approach is introduced to enhance deployment flexibility. Simulations validate the effectiveness of the proposed coverage strategy.
Journals
2026 EN
Zhou Nan · Zhu Zhongben · Qin Hongde
+4 more
ABSTRACT The development of maritime trade and operations has led to a gradual increase in maritime accidents. Research on the specificity of maritime search and rescue (SAR) missions is essential to improve mission efficiency; however, traditional SAR programs usually use predefined paths to conduct searches, which is difficult to meet the timeliness and uncertainty requirements. To solve the challenge, we propose a Boundary Adaptive Neural Network Coverage Path Planning Scheme based on Target Drift Prediction (BANCP‐TDP). The framework includes three modules: drift trajectory prediction, optimal region determination, and coverage search. First, the Limited Red‐billed Blue Magpie Optimizer Back Propagation drift model is used to predict the drift trajectory of the wrecked target. Subsequently, we use the Multiphysics Monte Carlo Gravitational Search prediction model to determine the distribution of targets at different moments and the optimal SAR region for guiding an autonomous underwater vehicle to carry out SAR missions. Then, we propose a BANCP for the SAR regions with complex boundaries, aiming to minimize the path length and maximize the coverage ratio. The comparative field experiments at Qingdao Jin Cao Gou reservoir and simulation results show that the proposed framework can effectively shorten path length while minimizing the repeated paths.
Journals
2026 EN
Tani Simone · Ruscio Francesco · Caiti Andrea
+1 more
ABSTRACT Underwater inspections of critical maritime infrastructures are still predominantly performed by human divers, exposing them to safety risks and yielding limited accuracy and repeatability. Autonomous Underwater Vehicles (AUVs) offer a promising alternative by removing humans from hazardous environments and enabling systematic, repeatable inspection operations. However, current AUV systems lack the necessary autonomy and typically rely on prior knowledge of the environment, limiting their applicability in real‐world scenarios. This study presents a visual–acoustic‐based framework aimed at overcoming these limitations and moving a step closer to fully autonomous inspection operations using AUVs. Designed for cost‐effective deployment on vehicles equipped with a minimal sensor suite—including a stereo camera, an acoustic range sensor, an Inertial Measurement Unit with magnetometers, a pressure sensor, and a Global Positioning System (used only on the surface)—the framework enables inspection of unknown underwater structures without human intervention. The main contribution lies in the integration of perception and navigation into a unified architecture, allowing the AUV to leverage the exteroceptive sensor not only for scene understanding but also to support real‐time control and mission adaptation. Perception data are combined with proprioceptive observations to adapt motion based on the environment, enabling autonomous management of the inspection mission and navigation with respect to the target. Furthermore, a mission manager coordinates all phases of the operation, from initial approach to structure‐relative navigation and visual data acquisition. The proposed solution was validated through a sea trial, during which an AUV autonomously inspected a harbor pier. The framework computed control actions in quasi‐real‐time to maintain a predefined safety distance, inspection velocity, and payload orientation orthogonal to the scene. These outputs were used online as feedback within the AUV's control loop. The underwater robot completed the inspection, maintaining mission references and ensuring effective target coverage, good‐quality optical data, and consistent three‐dimensional reconstruction. Overall, this experimental validation demonstrates the feasibility of the proposed framework and marks a significant milestone toward the deployment of fully autonomous AUVs for real‐world underwater inspection missions, even in the absence of prior knowledge about the structure.
Journals
2026 EN
Ganduri Krishna Vamshi · Pathri Bhargav Prajwal · Pammi S. V. N.
+1 more
ABSTRACT Swarm robots provide significant promise for autonomous exploration, disaster response, environmental monitoring, and military operations. Nevertheless, most existing platforms are limited to simulations or lack the full‐stack integration necessary for practical deployment. Although our prior simulation‐based research validated the theoretical viability of decentralized swarm behaviour, its actual execution continues to pose challenges. To bridge the gap, in the current research work, Woxbots, an economical and scalable swarm robotics platform designed for the experimental validation of pattern formation and collision‐aware route planning using velocity obstacle techniques, has been introduced. The current system was equipped with strong multiagent communication, real‐time obstacle avoidance, and velocity‐dependent trajectory regulation. The modular design, constructed using Raspberry Pi and ESP32 microcontrollers, guarantees dependable odometry, easy interface, and adaptable robot coordination. A PID controller improves dynamic responsiveness and trajectory accuracy. Extensive experimental trials with various autonomous agents confirm the platform's reliability, flexibility, and real‐time efficacy in dynamic, limited settings. Woxbots provide a cost‐effective and practical solution, facilitating the development of scalable swarm robotic systems for academic research, industrial automation, and mission‐critical operations.
Journals
2026 EN
Yang Xiaoyu · Wen Tongge · Zhang Kaiming
+3 more
ABSTRACT This study investigates the landing dynamics of a telescopic‐legged robotic rover on granular surfaces of small celestial bodies, addressing the challenges posed by its high‐degree‐of‐freedom structure. Using a custom module within the PolyDEM discrete element framework, the interaction between complex rigid bodies and nonspherical particles was accurately simulated and validated through ground‐based experiments. The results reveal that retracted legs exhibit superior damping performance on coarse gravel layers by increasing localized contact area, enhancing friction, and promoting internal particle rearrangement. Conversely, extended legs perform better on fine‐grained regolith by increasing penetration depth and enabling multi‐point interactions, which amplify energy absorption. Additionally, this study examines the effects of impact velocity and angle on rover stability, providing actionable insights for terrain‐specific deployment strategies. These findings advance our understanding of high‐DOF robotic systems in extraterrestrial environments and offer practical guidance for future mission planning.
Journals
2026 EN
An Xinyu · Shi Hongbo · Li Haoda
+4 more
ABSTRACT Autonomous underwater vehicles (AUVs) have become indispensable tools for exploring marine environments. However, most AUVs lack the ability to perform operations directly on the seabed. To address this limitation, we have designed a specialized AUV for seabed operations: the autonomous underwater helicopter (AUH). The AUH‐HY‐1 is a seabed operational vehicle specifically designed for complex near‐seabed exploration tasks. It adopts a disc‐shaped configuration and incorporates an Acoustic‐Inertial‐Optical integrated positioning and navigation system. The vehicle is equipped with multiple detection sensors and operates on a software framework developed using MOOS‐IvP, which provides robust mission management and control. The AUH‐HY‐1 operates in two modes: the traditional AUV mode and the AUH mode, where it collaborates with a Subsea Docking Station (SDS) for long‐term resident operations. A docking control strategy with orientation constraints ensures precise and reliable docking of the AUH. The integration of sonar with a YOLO‐based recognition algorithm enhances the vehicle's target detection performance. Field trials conducted in controlled pool environments, lakes, and open sea settings have demonstrated the AUH‐HY‐1's operational reliability and task execution capabilities, including waypoint‐based path planning, accurate docking, and seabed detection. It can perform near‐seabed detection tasks at a height of approximately 3 to 5 meters above the seabed, with a maximum speed of around 3 knots. The vehicle achieved a notable docking success rate of over 85% and a sonar image detector MAP of 80.2% with an average processing speed of 0.025 s per image. These results indicate that the AUH‐HY‐1 is well suited for supporting seabed exploration and advancing applications in marine technology and oceanographic research.
Journals
2026 EN
Zhang Yanwu · Kieft Brian · Messié Monique
+7 more
ABSTRACT Collaborative operation of multiple autonomous underwater vehicles (AUVs) can effectively achieve scientific goals that are hard to achieve by independently operated vehicles. Some science payloads are large, expensive, and need to be installed in the vehicle's nose cone. A vehicle can only carry one such payload. This specialization leads to heterogeneous fleets of vehicles that must work collaboratively to investigate unique oceanographic features using complementary payloads. We present a method of using acoustic tracking and messaging between two long‐range AUVs (LRAUVs) with different payloads for collaborative sampling and imaging of phytoplankton communities. The sampling vehicle acquires water samples from the peak chlorophyll layer. The imaging vehicle acoustically tracks the sampling vehicle and takes microscopic images of the surrounding water column to provide contextual optical evidence. Each vehicle transmits acoustic messages to inform the other vehicle about distance or mission status. In this collaboration, acoustic tracking and messaging enable co‐located synchronized sampling and imaging. The method was used in phytoplankton studies in Monterey Bay, California, in August 2024.