Trajectory planning and control of bionic dual‐arm underwater robotic manipulators (BDA‐URMs) are highly challenging due to the complex interactions between the manipulator’s base, its dual arms, and the nonlinear underwater dynamics. This study proposes a novel hybrid controller to enhance trajectory tracking and control of a BDA‐URM. The proposed hybrid control strategies integrate a proportional‐integral‐derivative (PID) controller and overwhelming control, which are tuned using various methods, including Ziegler–Nichols (Z‐N), genetic algorithm (GA), ant colony optimization (ACO), and particle swarm optimization (PSO) for generating precise motions. A comprehensive Simulink model is developed, incorporating the bionic dual‐arm, buoyancy, and hydrodynamic forces to analyze system dynamics. The PSO–based tuning of the hybrid controller demonstrated superior trajectory tracking performance compared to other methods. The controller achieved significant reductions in the integral of time multiplied by absolute error (ITAE) for different joints: link1–joint1 (Arm1), link1–joint2 (Arm2), link2–joint3 (Arm1), and link2–joint4 (Arm2), with improvements of 92.44%, 90.6%, 87.46%, and 89.21%, respectively. The proposed hybrid control method achieved the required stability with an exceptionally fast response time of 0.0089 s, making it highly effective for trajectory control in underwater manipulators.

Background Currently, hybrid parallel robots, which combine the advantages of both parallel and serial robots, are widely used in the world. The review conducted in the work showed the need for further development and research of hybrid parallel robots for orthopedic surgeries. Methods To identify relevant studies, a search was conducted in the PubMed, IEEE Xplore, Scopus, and Web of Science databases. Results An overview of hybrid parallel robots for orthopedic surgeries is presented, and recommendations for their further development are given. Conclusion As a result of the review, it was found that existing prototypes of hybrid parallel robots have good accuracy in bone resection, due to their rigid structure and large workspace. From the presented review, it was established that further development and research of hybrid parallel robots for orthopedic surgeries is necessary.

Accurate real-time kinematics model is very important for the control of a skid-steering mobile robot. In this study, the kinematics model of the skid-steering mobile robots was first designed based on instantaneous rotation centers (ICRs). Then, the extended Kalman filter (EKF) technique was applied to obtain the parameters of ICRs under the same specific terrain online. To adapt to different terrain environments, the fractal dimension-based SFTA (segmentation-based fractal texture analysis) method was used to extract features of different terrains, and the k-nearest neighbor (KNN) method was used to classify the terrains. In the case of real-time terrain recognition, the filter parameters of the EKF for estimating the ICRs are adjusted adaptively. Experiments on a real skid-steering mobile robot show that this method can quickly estimate the kinematics model of the robot in the case of terrain changes, and can meet the needs of practical applications. The average error of odometer estimation based on visual terrain classification is 0.06 m, while the average error of odometer estimation without terrain classification is 0.14 m.

Aiming at the problem of limited payload and endurance of micro-UAV, the target tracking algorithm based on monocular vision is proposed. Since monocular vision cannot directly measure distance between the UAV and the target, triangulation and triangle similarity are used to calculate the distance information. Then, a target tracking method based on Kalman filter and KCF is designed. The tracking result of KCF is modified by Kalman filter to solve the problem of target occlusion. Finally, the position of the target in the world coordinate system is calculated through the coordinate transformation matrix, which is used to control the UAV for tracking the moving target. In order to verify the feasibility of the algorithm, target size estimation and target tracking algorithms are carried out. The experimental results show that the proposed algorithm can track the moving target effectively under the condition of short-term occlusion.

Planar double-jointed robot is a kind of widely used robot. In the past decades, with the development of science and technology, planar double-jointed robot has a great breakthrough in many aspects, especially in the actual camera and attitude analysis. In recent years, pun-section manipulator has made great progress in technology, but its kinematic characteristics and the human body’s ability to move have a great gap. So, in the moving plane, we need to study how to improve its camera ability to find a more stable and effective camera mode, and to a certain extent, to meet its requirements in complex working conditions. Simulating the pose of two joints, we seek a more stable and effective camera mode to improve its moving speed, expand its moving space, and lay a solid foundation for its application. Planar double-jointed robot is the most representative one at present. It includes machinery, material, electronics, computer, sensor, drive, intelligent control, artificial intelligence, and so on. Because it is closer to the human body, more suitable for people’s work and work, so it does not need to change its environment, so it is regarded as having a high affinity for people’s machinery. Its characteristic is that it has the good adaptability and the flexibility, but the double joint camera’s support discontinuity enables it to be able to adapt each kind of complex situation well. It can not only climb the stairs but also in the messy ground smooth through and also in the inconvenient passage through. The aim of this paper is to analyze the unique advantages and irreplaceable characteristics of the planar double-jointed robot based on the bionic and mechanical research results. This paper analyzes the mechanical technology by means of literature review and actual data analysis. The experimental results show that the biggest difference between the two articulated robots and other robots is that they have two human-like joint motions.

This study investigates a guidance method that will allow the small unmanned helicopter to follow the predefined horizontal smooth path. A stable nonlinear guidance law, which needs the information of the inertial position and groundspeed of the helicopter and the implicit function of the desired path, is designed to generate the reference course rate command based on the concept of the vector field. The asymptotic approximation to the desired path with bounded following errors has also been demonstrated by using the Lyapunov stability arguments. Some conditions for guaranteeing the stability have been extended. Simulations on following four types of planar paths, i.e., the square, circular, elliptic, and cubic curve paths, have verified the effectiveness of the proposed method. The predefined square path following performance of the proposed vector field-based method is compared with another two guidance laws, which are based on the PD-like and fuzzy logic control. The comparison shows that the proposed method can guide the helicopter to follow the predefined path most smoothly. The maximum overshoot by using the proposed method is less than 0.016 meters, while those by using the other two methods are all larger than 0.80 meters. Moreover, the vector field-based method will cost the least time for the vehicle to converge to the predefined path.