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Elastic properties of classical bulk materials can hardly be changed or adjusted in operando, while such tunable elasticity is highly desired for robots and smart machinery. Although possible in reconfigurable metamaterials, continuous tunability in existing designs is plagued by issues such as structural instability, weak robustness, plastic failure and slow response. Here we report a metamaterial design paradigm using gears with encoded stiffness gradients as the constituent elements and organizing gear clusters for versatile functionalities. The design enables continuously tunable elastic properties while preserving stability and robust manoeuvrability, even under a heavy load. Such gear-based metamaterials enable excellent properties such as continuous modulation of Young’s modulus by two orders of magnitude, shape morphing between ultrasoft and solid states, and fast response. This allows for metamaterial customization and brings fully programmable materials and adaptive robots within reach. A design paradigm to create robust robotic metamaterials using versatile gear clusters is demonstrated. It enables intriguing programmability of elastic properties and shape while preserving stability for intelligent machines.

Recently, unmanned aerial vehicles (UAVs), also known as drones, have come in a great diversity of several applications such as military, construction, image and video mapping, medical, search and rescue, parcel delivery, hidden area exploration, oil rigs and power line monitoring, precision farming, wireless communication and aerial surveillance. The drone industry has been getting significant attention as a model of manufacturing, service and delivery convergence, introducing synergy with the coexistence of different emerging domains. UAVs offer implicit peculiarities such as increased airborne time and payload capabilities, swift mobility, and access to remote and disaster areas. Despite these potential features, including extensive variety of usage, high maneuverability, and cost-efficiency, drones are still limited in terms of battery endurance, flight autonomy and constrained flight time to perform persistent missions. Other critical concerns are battery endurance and the weight of drones, which must be kept low. Intuitively it is not suggested to load them with heavy batteries. This study highlights the importance of drones, goals and functionality problems. In this review, a comprehensive study on UAVs, swarms, types, classification, charging, and standardization is presented. In particular, UAV applications, challenges, and security issues are explored in the light of recent research studies and development. Finally, this review identifies the research gap and presents future research directions regarding UAVs.

Birds morph their wing shape to accomplish extraordinary manoeuvres 1 – 4 , which are governed by avian-specific equations of motion. Solving these equations requires information about a bird’s aerodynamic and inertial characteristics 5 . Avian flight research to date has focused on resolving aerodynamic features, whereas inertial properties including centre of gravity and moment of inertia are seldom addressed. Here we use an analytical method to determine the inertial characteristics of 22 species across the full range of elbow and wrist flexion and extension. We find that wing morphing allows birds to substantially change their roll and yaw inertia but has a minimal effect on the position of the centre of gravity. With the addition of inertial characteristics, we derived a novel metric of pitch agility and estimated the static pitch stability, revealing that the agility and static margin ranges are reduced as body mass increases. These results provide quantitative evidence that evolution selects for both stable and unstable flight, in contrast to the prevailing narrative that birds are evolving away from stability 6 . This comprehensive analysis of avian inertial characteristics provides the key features required to establish a theoretical model of avian manoeuvrability. Analysis of inertial characteristics across 22 bird species shows that evolution has selected for avian manoeuvrability using both stable and unstable flight dynamics.

In this study, we conducted turning tests with rudder angles ± 35 ∘ and ± 20 ∘ / 20 ∘ zig-zag maneuver tests in deep and shallow water using a model of a 3,600 TEU container ship called KCS. Through the comparison of these test results with the free-running test results of three other ships, the shallow-water effect on the maneuverability was investigated. The shallow-water effects obtained during the turning and zig-zag maneuvers are as follows: Turning: The advance ( A D ) decreases slightly when the water depth-to-ship draft ratio ( h / d ) is approximately 2.0 and increases significantly as the water depth decreases. The tactical diameter ( D T ) (up to h / d = 2.0 ) is approximately the same as that in deep water and becomes significantly larger when h / d becomes smaller than 2.0. Thus, there is a slight difference in the appearance of the shallow-water effects in A D and D T . Zig-zag maneuvers: The overshoot angle increases slightly near h / d = 2.0 compared with that in deep water and becomes significantly smaller as the water depth becomes shallower. The forward distance ( l 20 ), until reaching the heading + 20 ∘ / - 20 ∘ after steering, was approximately the same as that in deep water or decreased slightly, until approximately h / d = 2.0 . Furthermore, it increased as the water depth decreased. This is because the course stability of the ship deteriorated at approximately h / d = 2.0 .

The continuous growth in maritime traffic and recent developments towards autonomous navigation have directed increasing attention to navigational safety in which new tools are required to identify real-time risk and complex navigation situations. These tools are of paramount importance to avoid potentially disastrous consequences of accidents and promote safe navigation at sea. In this study, an adaptive ship-safety-domain is proposed with spatial risk functions to identify both collision and grounding risk based on motion and maneuverability conditions for all vessels. The algorithm is designed and validated through extensive amounts of Automatic Identification System (AIS) data for decision support over a large area, while the integration of the algorithm with other navigational systems will increase effectiveness and ensure reliability. Since a successful evacuation of a potential vessel-to-vessel collision, or a vessel grounding situation, is highly dependent on the nearby maneuvering limitations and other possible accident situations, multi-vessel collision and grounding risk is considered in this work to identify real-time risk. The presented algorithm utilizes and exploits dynamic AIS information, vessel registry and high-resolution maps and it is robust to inaccuracies of position, course and speed over ground records. The computation-efficient algorithm allows for real-time situation risk identification at a large-scale monitored map up to country level and up to several years of operation with a very high accuracy.

The congestion of waterways can easily lead to traffic hazards. Moreover, according to the data, the majority of sea collisions are caused by human error and the failure to comply with the Convention on the International Regulation for the preventing Collision at Sea (COLREGs). To avoid this situation, ship automatic collision avoidance has become one of the most important research issues in the field of marine engineering. In this study, an efficient method is proposed to solve multi-ship collision avoidance problems based on the multi-agent reinforcement learning (MARL) algorithm. Firstly, the COLREGs and ship maneuverability are considered for achieving multi-ship collision avoidance. Subsequently, the Optimal Reciprocal Collision Avoidance (ORCA) algorithm is utilized to detect and reduce the risk of collision. Ships can operate at the safe velocity computed by the ORCA algorithm to avoid collisions. Finally, the Nomoto three-degrees-of-freedom (3-DOF) model is used to simulate the maneuvers of ships. According to the above information and algorithms, this study designs and improves the state space, action space and reward function. For validating the effectiveness of the method, this study designs various simulation scenarios with thorough performance evaluations. The simulation results indicate that the proposed method is flexible and scalable in solving multi-ship collision avoidance, complying with COLREGs in various scenarios.

The aging and deterioration of structures such as bridges or buildings is becoming an urgent social issue; regular inspections for the preservation of the structures are needed, but it means high cost especially in terms of safety for workers due to the difficulty to access. Visual inspection of workers can be replaced by using basic drones, which share many advantages such as speed, safety for the workers, cost-effectiveness, share-ability with more stakeholders instantly and manoeuvrability by making use of automated flights. A visual inspection made by drone is the first part of a complex survey campaign, and its use allows planning experimental investigation for diagnostic. This study analyses both the positive and negative aspects of the use of drones for structural inspection, underlying the low cost, immediacy, instant measurement and the possibility of developing a 3D model, with an acceptable level of definition and reliable for a diagnostic process. Two application examples are proposed.

The importance of the uncertainty quantification in ship maneuverability prediction is expounded. An efficient method for the uncertainty quantification problem, the Non-Intrusive Polynomial Chaos (NIPC) method, is introduced. A 3-DOF MMG model is adopted to carry out simulations of 35° turning circle tests and 10°/10° zig-zag tests for a KCS container ship model. The effects of the uncertainty of the hull-related hydrodynamic derivatives in the MMG model on the maneuverability parameters, i.e., the advance, the tactical diameter, the initial turning time and the overshoot angles are analyzed quantitatively, and the sensitivities of these parameters to the hydrodynamic derivatives are determined. The results are compared with those obtained by the Monte Carlo (MC) method. It is shown that the NIPC method is much better than the MC method in terms of the convergence with respect to the number of samples, and the computation accuracy of the NIPC method is higher than that of the MC method under the same number of samples; the considered maneuverability parameters are most sensitive to the uncertainty of the yaw moment related hydrodynamic derivatives, and least sensitive to that of the longitudinal force related ones. The feasibility of the NIPC method in the uncertainty quantification of ship maneuverability prediction is proved, which provides a novel approach to analyze the influence of the accuracy of the hydrodynamic derivatives on ship maneuverability prediction.

The maneuverability of ships is influenced by several factors, including ship design, size, propulsion system, hull shape, and external conditions such as wind, waves, and currents. The size, shape, and arrangement of the hull, rudder, and propeller are decisive for maneuverability. Hydrodynamic forces such as bank effect and squat significantly impact the maneuverability of large ships in narrow channels. With the increasing trend of building ever-larger ships, the demand to evaluate the maneuvering performance of the ship at the design stage has become more critical than ever. Both experimental and computational methods are used to obtain accurate maneuvering characteristics of vessels. In this study, the methods for predicting ship maneuvering characteristics are analyzed using a systematic review based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA). This article contributes to a deeper understanding of the hydrodynamic capabilities of ships and identifies possible future challenges in the field of ship hydrodynamics. The findings inform educators and the shipping industry about the importance of predicting the maneuvering performance of ships, with an emphasis on the education and training of seafarers needed to make timely decisions in critical situations.

This paper proposes a guidance law based on trajectory prediction, aiming to address the difficulty of traditional guidance laws in meeting high-speed and highly maneuverable vehicles. The unscented Kalman filtering (UKF) technique is employed to estimate the target’s motion and predict the virtual impact point using the Singer model and measuring model. The midcourse guidance law is applied to the virtual target, taking into account the constraint of the intersection angle, while the terminal guidance utilizes modified proportional guidance. To mitigate the overload chattering in the transition sections of both midcourse and terminal guidance, the distance is used to modify the transition section of the terminal guidance. Simulation results demonstrate that the proposed guidance law effectively reduces both the encounter angle and the required maneuvering. Furthermore, to minimize midcourse guidance errors, the prediction results of the virtual target are continually updated during the trace process. This method can also be applied to trail other highly maneuverable targets.