Due to underwater light absorption and scattering, underwater images often suffer from color distortion and low contrast. However, existing underwater image enhancement methods can only solve the problem of underwater image degradation in a specific scene, and do not consider the impact of dynamic changes in water depth and water quality on underwater image degradation. In order to solve the above problems, this paper proposes a multi-channel adaptive fusion underwater image enhancement algorithm. Firstly, in order to alleviate the color distortion issue caused by light attenuation, this paper proposes a gridded adaptive channel compensation algorithm. Subsequently, the compensated image is used for multi-channel image enhancement. The first channel image is the enhanced result of the compensated image using the local entropy-constrained gray world algorithm proposed in this paper and the second channel image is the enhanced result of the first channel image using the contrast limited adaptive histogram equalization(CLAHE) algorithm. Next, the saliency weight image and brightness weight image of the two-channel images are calculated respectively. Finally, in order to combine the information advantages of different channel images, this paper adopts Laplacian-Gaussian pyramid to fuse the two-channel enhanced images and their corresponding weight images to obtain the final enhanced image. Experiments on three datasets, LSUI, UIEB and RUIE, show that the underwater images processed by the algorithm proposed in this paper have a good improvement in color and contrast, and robustness is better than the comparative methods. The UIQM value of the enhanced images is 126.844% higher than the original images, the UCIQE value is 66.370% higher than the original images, and the number of ORB feature points is 95.862% higher than the original images. Results available at https://drive.google.com/file.

To solve the trajectory planning problem of the flexible manipulator under various constraints such as end-camera attitude, drive space, and obstacles during video inspection along a continuous path in narrow three-dimensional space, this paper proposes a time-optimal trajectory planning method from the initial configuration to the final configuration. The trajectory planning problem is transformed into a multi-constraint optimization problem. First, to realize continuous video inspection in an unstructured complex environment, by analyzing the geometric model of the two-segment flexible manipulator with a camera at the end, the pose constraints between the camera and the shooting surface are formulated by the space vector method, the driving constraints are formulated based on kinematics, and the obstacle constraints are formulated by space mapping. Then, a multi-constraint optimization model is constructed to generate the smooth trajectory of the drive cable of the flexible manipulator by minimizing the total time of continuous path motion. Compared with the conventional point-to-point collision avoidance planning solution method, this paper starts from the global perspective and investigates the less considered continuous path trajectory planning problem; also, the swarm intelligence algorithm artificial jellyfish search algorithm (JS) is employed to optimize the solution and find the minimum time trajectory conforming to a variety of complex constraints. Finally, a simulation is conducted with CoppeliaSim, and the continuous path video inspection experiment is carried out in the 500KV GIS (Gas Insulated Switchgear) equipment, the simulation and experimental results indicate that the planned drive cable trajectory is smooth and effective. In addition, each path point is tracked and obstacles are avoided safely. When the flexible manipulator moves along the whole path, the pose of the camera satisfies the relaxed attitude constrain The proposed method can guide the two-segment flexible manipulator to complete the continuous video inspection task of the GIS cavity wall and conductive column surface.

To address the finite-time tracking control problem for fractional-order nonlinear systems (FONSs) with actuator faults and external disturbance, a novel strategy of the finite-time adaptive fuzzy fault-tolerant controller is presented in this paper by utilizing the finite-time stability theory and fractional-order dynamic surface control scheme combined with backstepping method. A new lemma is developed for analyzing the finite-time stability of FONSs in terms of fractional differential inequality, which modifies some existing results. Fuzzy logic systems are adopted to identify unknown nonlinear characteristics in FONS. In order to compensate for the influence of unknown external disturbance and estimation error for fuzzy logic systems, an auxiliary function is employed to estimate the upper bound of parameters online. Furthermore, a global coordinate transformation is first introduced initially to decouple the fractional-order dynamic system of a specific class of underactuated single-link flexible manipulator systems, thereby transforming it into lower triangular systems. Simulation analyses and experimental results verify the feasibility and effectiveness of finite-time tracking control algorithm.

Aiming at the challenge of trajectory planning for a continuum manipulator in the confined spaces of gas-insulated switchgear (GIS) chambers during intelligent operation and maintenance of power equipment, this paper proposes a configuration space (C-space) obstacle-avoidance planning method based on an improved RRT-Connect algorithm. By constructing a virtual joint-space obstacle map, the collision-avoidance problem in Cartesian space is transformed into a joint-space path search problem, significantly reducing the computational burden of frequent inverse kinematics solutions inherent in traditional methods. Compared to the RRT-Connect algorithm, improvements in node expansion strategies and greedy optimization mechanisms effectively minimize redundant nodes and enhance path generation efficiency: the number of iterations is reduced by 68% and convergence speed is improved by 35%. Combined with polynomial-driven trajectory planning, the method successfully resolves and smoothens driving cable length variations, achieving efficient and stable control for both the end-effector and arm configuration of a dual-segment continuum manipulator. Simulation and experimental results demonstrate that the proposed algorithm rapidly generates collision-free arm configuration trajectories with high trajectory coincidence in typical GIS chamber scenarios, verifying its comprehensive advantages in real-time performance, safety, and motion smoothness. This work provides theoretical support for the application of continuum manipulator in precision operation and maintenance of power equipment.