Unmanned surface vesssel (USV) has been widely applied due to its advantages in the military reconnaissance and resources exploration. Path planning is one of the critical issues for USV applications, which usually includes global and local path planning methods. However, individual global path planning algorithms may not be easy to detect the dynamic obstacles in the environment, and individual local path planning algorithms may not always guarantee the existence of the feasible solution for the complex environment. Therefore, a hybrid algorithm which effectively combines global and local path planning is proposed in this paper to overcome these drawbacks. The A* algorithm is used in the global path planning to generate a global path for USV to reach the target point. The dynamic window algorithm (DWA) is used in the local path planning to avoid the dynamic obstacles and track the global path by following the local target point which is the intersection of the global and local path planning. The weight coefficient considering sea state is added in the objective function of DWA, where the security of USV can be guaranteed by reducing the weight of velocity and increasing the weight of distance when the sea state level becomes high. Thus, USV can get a global optimal path and reach the target point in complex environment with dynamic obstacles and ocean currents via the proposed hybrid algorithm, and the comparative simulation is carried out to verify the effectiveness and advantage of the proposed method.

Unmanned surface vessel (USV) has been widely applied due to its advantages in the maritime security inspection and resources exploration. Good trajectory tracking performance is a critical issue in the control design of USV. However, most of the existing controllers are designed based on linear dynamic model or do not well consider the integrated effect nonlinearities, various uncertainties (e.g., modeling error and parameter variations) and external disturbance (wind, wave, current, etc). In this paper, a nonlinear dynamic model is established for USV with the integrate consideration of these issues, and a disturbance-observer-based sliding mode control design is subsequently proposed to achieve the good tracking performance, where the observer is to estimate and compensate the modeling uncertainties and external disturbance. Theoretically, the stability of the observer and overall closed-loop system of USV are guaranteed via the Lyapunov theorem. The comparative simulation is carried out, and the results show the fast response, better transient performance and robustness of the proposed control design.

Recent years, triboelectric nanogenerators (TENGs) have attracted increased attention from researchers worldwide. Owing to their conductivity and triboelectric characteristics, metal materials can be made as both triboelectric materials and conductive electrodes. However, the surface of typical metals (such as copper, aluminum, and iron) is likely to be corroded when the sweat generated by human-body movement drops on the surface of TENGs, as this corrosion is detrimental to the output performance of TENGs. In this work, we proposed a novel corrosion-resistant copper–nickel based TENG (CN-TENG). Copper–nickel alloy conductive tape and polytetrafluoroethylene (PTFE) tape played the role of the triboelectric materials, and polymethyl methacrylate (PMMA) was utilized as the supporting part. The conductive copper–nickel alloy tape also served as a conductive electrode. The open-circuit voltage (V_OC) and short-circuit current (I_SC) can arrive at 196.8 V and 6 μA, respectively. Furthermore, peak power density values of 45 μW/cm² were realized for the CN-TENG. A series of experiments confirmed its corrosion-resistant property. The approximate value of V_OC for the fabricated TENG integrated into the shoe reached 1500 V, which is capable of driving at least 172 high-power LEDs in series. The results of this research provide a workable method for supporting corrosion-resistant self-powered wearable electronics.

Unmanned surface vessel(USV) has been applied in the maritime security inspection and resources exploration to execute complex works with its advantages in automation and intelligence. While the nonlinear USV working in the complex ocean environment, the good trajectory tracking performance is an important capacity. However, the nonlinearity, modeling uncertainties (e.g., modeling error and parameter variations) and external disturbance (wind, wave, current, etc) are the main difficulties, which deteriorates the control performance. To solve this issue, most existing algorithms for USV's tracking have been developed based on the linearization of the USV's nonlinear dynamic model at specific equilibrium point. However, the integrated effect of nonlinearities, modeling uncertainties and external disturbance has not been well considered, which can degrade the USV's tracking performance. Therefore, to achieve the good tracking performance for USV, a nonlinear dynamic model is strictly derived in this paper with the integrate consideration of abovementioned issues, and an adaptive sliding mode control design using RBFNN(Radial Basis Function Neural Network) and disturbance-observer is subsequently developed, where a RBFNN approximator is designed to approximate and compensate modeling uncertainties, and a disturbance-observer is designed to estimate and compensate the effect of the external disturbance. Furthermore, the global stability of the overall closed-loop system of USV are strictly guaranteed. The comparative simulation is carried out to validate the fast response, better transient performance and robustness of our proposed control design via comparing with the existing methods.

The cooperative motion of multiple mobile robots has attracted wide attention due to its advantages in military, marine and aerospace fields, and formation control has become a significant technology in the realization of these tasks. However, most of the existing formation control designs of mobile robots do not consider the practical obstacles in the environment, and the maintenance of both formation and trajectory tracking while confronting the obstacles is still a challenging issue. Therefore, in this paper, a virtual-structure-based formation control approach is designed with obstacle avoidance for a system with multiple mobile robots. The basic trajectory is generated for each robot in the group and parameterized to keep the group in formation. A trajectory generator is then established regarding the obstacles, where a potential function is designed to adjust the basic trajectory and replan the reference trajectory to achieve obstacle avoidance. Then, a novel design for the path parameter is proposed to improve the performance of the robot group when encountering obstacles. Finally, a tracking controller is designed to achieve good tracking performance for robots, and the guaranteed performance is achieved via the Lyapunov theorem. A comparative simulation with three sets is carried out, where an objective function $F_{obj}$ is designed to evaluate the tracking performance in the presence of obstacles. Besides this, a real experiment is implemented to further verify the effectiveness. The simulation and experimental results verify the good formation and tracking performance of the proposed design for a system with multiple mobile robots with obstacle avoidance.

Electro hydrostatic actuator (EHA) has been successfully developed for flight control applications to replace the cumbersome centralized hydraulic system. It also has excellent potential for ocean applications due to its advantages on miniaturization and energy-savings. One of the special technologies for EHA’s underwater application is pressure compensation, which is used to equalize the return pressure of the hydraulic system and the seawater pressure. This paper investigates the modeling and control design of underwater EHA to improve performance, especially considering the effect of additional pressure compensator and uncertain external load. The nonlinear hydraulic model is extended by the dynamic characteristics of the pressure compensator. Two low-order extended state observers were constructed to cope with the external load fore and the effect of the pressure compensator, respectively. The backstepping methods were designed to guarantee the robust stability of the entire high-order nonlinear hydraulic system. Finally, the theoretical proving and simulation on Matlab/Simulink are conducted to demonstrate the high tracking performance of the proposed control strategy.