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. INDEX TERMS Hybrid path planning, dynamic window algorithm, unmanned surface vehicles, A* algorithm.

The bilateral teleoperation technique has drawn much attention with its attractive superiority to implement the tasks in hazardous environments. Transmission delays and uncertainties are the two main challenges in the nonlinear bilateral teleoperation system to guarantee stability and achieve good transparency performance (including position tracking and force feedback) simultaneously. In this paper, a radial basis function neural network (RBFNN)-based adaptive sliding mode control design is developed for the nonlinear bilateral teleoperation system with transmission delays and uncertainties. For details, the reference trajectory producer is designed in both the master and slave sides to produce the passive reference trajectories for the tracking of master/slave manipulators. The RBFNN-based adaptive sliding mode controller is designed separately for the master and slave to achieve the good tracking performance under system uncertainties. To mitigate the negative effect of transmission delays on the system's stability, a projection mapping by saturation function is applied in the master side to guarantee the boundedness of the delayed environmental torque. Thus, the global stability and the good transparency performance with both position tracking and force feedback can be simultaneously achieved for our proposed method. The comparative experiment is carried out, and the results show the significant performance improvement with our proposed control design. INDEX TERMS Bilateral teleoperation, adaptive sliding mode control, neural network, transmission delays, uncertainties.

Underwater manipulators are important robotic tools in the exploration of the ocean environment. Up to now, most existing underwater manipulators are rigid and with fixed 5 or 7 degrees of freedom (DOF), which may not be very suitable for some complicated underwater scenarios (e.g., pipe networks, narrow deep cavities, etc.). The biomimetic concept of muscles and tendons is also considered as continuum manipulators, but load capacity and operation accuracy are their essential drawbacks and thus limit their practical applications. Recently, the cable-driven technique has been developed for manipulators, which can include numerous joints and hyper-redundant DOF to execute tasks with dexterity and adaptability and thus they have strong potential for these complex underwater applications. In this paper, the design of a novel cable-driven hyper-redundant manipulator (CDHRM) is introduced, which is driven by multiple cables passing through the tubular structure from the base to the end-effector, and the joint numbers can be extended and decided by the specific underwater task requirements. The kinematic analysis of the proposed CDHRM is given which includes two parts: the cable-joint kinematics and the joint-end kinematics. The geometric relationship between the cable length and the joint angles are derived via the established geometric model for the cable-joint kinematics, and the projection relationship between the joint angles and end-effector’s pose is established via the spatial coordinate transformation matrix for the joint-end kinematics. Thus, the complex mapping relationships among the cables, joints and end-effectors are clearly achieved. To implement precise control, the kinematic control scheme is developed for the CDHRM with series-parallel connections and hyper-redundancy to achieve good tracking performance. The experiment on a real CDHRM system with five joints is carried out and the results verify the accuracy of kinematics solution, and the effectiveness of the proposed control design. Particularly, three experiments are tested in the underwater environment, which verifies its good tracking performance, load carrying and grasping capacity.

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 Fobj 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.

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