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One‐dimensional thrust vectoring turbojet vertical takeoff and landing (VTOL) aircraft have attracted research attention due to their high thrust‐to‐weight ratios and their solution for the slow speed response of turbojet engines. However, there are some uncertainties and physical limitations in their systems, such as external disturbances, unknown parameters and input saturation. To improve the accuracy and convergence speed of trajectory tracking, a fixed‐time control method that is robust to saturation is proposed. The system dynamics are established, and an auxiliary system is built within a fixed time control framework to address the influence of input saturation and increase the error convergence rate. Nonsingular fast terminal sliding mode technology is combined with a few adaptive laws to ensure the robustness of the closed‐loop system against dynamic uncertainties and improve the precision of steady‐state control. The stability of the control system is proven based on Lyapunov, and the controller parameters are optimized based on particle swarm optimization (PSO). The proposed method based on fixed‐time stability guarantees that the states of the closed‐loop system can reach the residual set around zero within the designed time, and an expression for the upper bound on the convergence time is given. Finally, numerical simulations demonstrate the superiority of the proposed method based on the error integral criterion. [ABSTRACT FROM AUTHOR]

Retinal surgery requires enclosed spatial constraints to improve the safety and success of the surgery. Herein, a shared control method is proposed for master–slave robot systems, utilizing tubular guidance constraints based on a novel potential field function to optimize the commands of the surgeon. Within the tube, attractive constraints intensify with increasing task error and approach infinity at the boundary of the tube. This ensures that the surgery is confined within a closed tubular space. Haptic feedback provides force cues to inform the surgeon about the feasibility of the input commands. Theoretical derivations demonstrate that the entire closed‐loop system is passive. Two simulation experiments are conducted on the ophthalmic surgery robot platform to evaluate the functionality of the proposed method. The experimental results indicate that translational errors are kept less than certain predefined values. Furthermore, the proposed method outperforms the comparison method in terms of task accuracy and efficiency. [ABSTRACT FROM AUTHOR]

In nature, gliding birds frequently execute intricate flight maneuvers such as aerial somersaults, perched landings, and swift descents, enabling them to navigate obstacles or hunt prey. It is evident that birds rely on different wing–tail configurations to accomplish a wide range of aerial maneuvers. For traditional fixed‐wing unmanned aerial vehicles (UAVs), pitch control primarily comes from the tail's elevators, while adjusting flight lift and drag involves deploying wing flaps. Although these designs ensure reliable flight, they compromise the drones' maneuverability to maintain longitudinal stability. Therefore, the study introduces a biomimetic morphing wing UAV, and presents a pitch control strategy that simultaneously engages morphing wings, ailerons, and tail elevators. The pull‐up maneuver tests indicate that the proposed control method results in a pitch rate that is approximately 2.5 times greater than when using only the elevator control. A closed‐loop control system for the drone is also established. The closed‐loop flight experiment, which tracks a 45° pitch angle, demonstrates the effectiveness of the proposed coupled control method in adjusting the flight attitude. In addition, during cruising, the UAV employs three configurations, straight wing, forward‐swept wing, and back‐swept wing, to cater to different mission objectives and augment its flight capabilities. [ABSTRACT FROM AUTHOR]

This paper presents a complete planner and controller scheme to achieve balance and walking for a biped robot, which does not need to distinguish the robot's dynamic model parameters. The high-level planner utilizes model predictive control to optimize both the foothold location and step duration based on the Divergent Component of Motion (DCM) model to enhance the robustness of generated gaits. For low-level control, we use quadratic programming (QP) to optimize the contact force distribution under the contact constraints to achieve the virtual wrench exerted on the base of the robot. Then, the joint torques sent to the robot are derived from three parts: first, the torques mapped from the contact force; second, the swing leg tracking; and third, the stance foot stabilization. The simulation and experiment on BRUCE, a miniature bipedal robot from Westwood Robotics (Los Angeles, CA, USA), testify to the performance of the control scheme, including push recovery, Center of Mass (CoM) tracking, and omnidirectional walking. [ABSTRACT FROM AUTHOR]

Modular robots have unique advantages in handling faults and improving their robustness due to their self‐reconfiguration capacity and homogeneous interchangeability. When locked joint failure occurs in modular robots, the distribution of the failed modules will affect the manipulation capacity of the robot. In this article, a novel self‐reconfiguration method that utilizes only the remaining resources available to mitigate the damage caused by module joint failures is proposed. The key node configuration is searched by the particle swarm optimization (PSO) algorithm, and then the collision‐free reconfiguration path is planned by the rapidly exploring random trees (RRT) algorithm. The proposed method not only handles single‐module lockup failure but can also be expanded to multi‐module lockup failures, fully improving the fault tolerance of the modular robot. The method is deployed on the hardware, and the feasibility of the algorithm is verified by self‐reconfiguration experiments containing faulty modules. [ABSTRACT FROM AUTHOR]

Supernumerary robotic limbs (SRLs) are a new type of wearable robot that add artificial limbs to the human body to perform collaborative tasks. In contrast with exoskeletons, SRLs are kinematically independent of human limbs, allowing the wearer to overcome the limitations of human physiological ability, such as realizing the expansion of space in the human body, rather than enhancing existing limbs. In this study, a lightweight and compact hexagonal reconfigurable lower‐limb SRL system is proposed to assist human locomotion in daily activities, including walking, crouching, and stair climbing. To adapt to multiple scenarios, the hexagonal mechanism can be adjusted to different configurations including convex hexagonal configuration, pentagonal configuration, and concave hexagonal configuration. To achieve more optimized performance of different configurations, the optimization for identifying the optimal dimensions of each link was carried out. Subsequently, the detailed design methodology and specifics are presented. Finally, the load and wearing performance experiments were evaluated. The experiment results demonstrated that the tested maximum load in different configurations exceeded 90% of the simulated value and the entire equipment has a good wearing adaptability. This study may inspire the design of other lower‐limb SRLs and provide efficient solutions for stable support assistance in various scenarios. [ABSTRACT FROM AUTHOR]