For the formation and obstacle avoidance challenges of UAVs (unmanned aerial vehicles) in complex scenarios, this paper proposes an improved collaborative strategy based on APF (artificial potential field). This strategy combines graph theory, the Leader–Follower method, and APF. Firstly, we used graph theory to design formation topology and dynamically adjust the distances between UAVs in real time. Secondly, we introduced APF to avoid obstacles in complicated environments. This algorithm innovatively integrates the Leader–Follower formation method. The design of this attractive field is replaced by the leader’s attraction to the followers, overcoming the problem of unreachable targets in APF. Meanwhile, the introduced Leader–Follower mode reduces information exchange within the swarm, realizing a more efficient “few controlling many” paradigm. Afterwards, we incorporated rotational force to assist the swarm in breaking free from local minima. Ultimately, the stability of the integrated formation strategy was demonstrated using Lyapunov functions. The feasibility and effectiveness of the proposed strategy were validated across multiple platforms.

Addressing the issue of UAV flight path planning, this paper proposes an enhanced particle swarm algorithm for UAV path planning based on Levy flight. The incorporation of adaptive inertia weight tuning and Levy flight approach aims to mitigate the problem of premature convergence towards local optima in algorithms for particle swarm optimization. Firstly, a UAV path planning model is established considering the actual spatial environment and body dynamics constraints during UAV flight. A path evaluation function is constructed by combining the cost of path length and flight constraints, transforming the flight path planning problem into a minimum optimization problem for resolution. Secondly, the performance of UAV path planning is significantly improved by incorporating a particle swarm algorithm with an adaptive parameter adjustment mechanism, in addition to integrating the Levy flight strategy. Comparative analysis against classical PSO algorithms and linear decreasing PSO algorithms verifies the effectiveness of our proposed approach. The simulation results show that compared with the traditional particle swarm optimization algorithm, the local search ability of the proposed algorithm is improved by l5%, and the search accuracy is greatly improved.

In this paper, a novel 3D (three-dimensional) soft-landing dynamic theoretical model of a legged lander is developed in detail as well as its numerical solution process. The six degrees of freedom motion (6-DOF) of the base model of the lander with mass center offset setting is considered in the model as well as the spatial motion (3-DOF) of each landing gear. The characteristics of the buffering force, the footpad–ground contact, and the inter-structure friction are also taken into account during the motion of each landing gear. The direct constraint violation correction is used to control the constraint stabilization of the nonlinear dynamic equation. Comparative studies between the results from the proposed model and the simulated model (built in MSC Adams) under four classical load cases show the validity of the model. Additionally, the influences of different types of contact force models, friction force models, and a friction correction model used in the soft-landing dynamic model are further investigated as a step toward understanding the soft-landing dynamic performance and the feasibility of the dynamic model method of a legged lander. The results indicate that a precise lateral force model of the footpad–ground contact is necessary to obtain the soft-landing performance of one lander during soft landing.

Surface accuracy is one of the most crucial indicators for evaluating the performance of a large deployable antenna. It depends on the accuracy of the truss structure of the truss antenna. This paper presents a novel method for accurate analysis of a large deployable truss antenna with 3D joint clearances. The proposed method does not depend on the structure’s style, which is suitable for general multi-closed-loop structures. Firstly, the clearance model of the truss structure is established using a vector description. Then, an error transfer path analysis method is proposed for the multi-closed-loop structure. The distribution probability of the truss antenna’s surface accuracy is also obtained. The efficiency of the method is validated through a numerical example of a planar mechanism with a multi-closed loop. The proposed method is also applied to analyze the surface accuracy of the large deployable antenna with a parabolic cylindrical truss.

Distributed time-varying formation technology for multi-agent systems is recently become a research hotspot in formation control field. However, the formation reconfiguration control technology for agents that randomly appeared to fail during maneuvers is rarely studied. In this paper, the topological relations between intelligence are designed by graph theory to simplify the cooperative interaction between multi-agent systems. Moreover, this paper constructs the time-varying configuration of the target formation based on the rigidity graph theory and leader–follower strategy. Drawing on the establishment of the expert experience database in a collaborative process, we innovatively propose the establishment of a graphic library to help the multi-agent system quickly form an affine transformation as soon as it is disabled. Secondly, the improved Hungarian algorithm is adopted to allocate the target point when the first failure occurs. This algorithm incorporates a gradient weighting factor from the auction algorithm to improve the speed of system reconfiguration with minimum path cost. On this basis, a distributed multi-agent control law based on consistency theory is established, and the system’s stability can be guaranteed via Lyapunov functions. Finally, the simulation results demonstrate the feasibility and effectiveness of the proposed formation reconfiguration control algorithm in a collaborative environment.

This article introduces a UAV (unmanned aerial vehicles) formation flight control based on an improved APF (artificial potential field). Utilizing the Leader-Follower formation approach, the path of the leader UAV is pre-planned, and followers maintain the designated formation configuration. To avert collisions between UAVs, an APF is integrated to facilitate emergency avoidance. Considering the environmental scenario with obstacles, distinct artificial repulsive fields are established for various obstacles. In order to tackle the issue of unreachable goals within the APF method, an additional term related to the target is introduced. This addition effectively eliminates the impact of obstacles surrounding the target point. The error between the follower's actual and expected positions is fed into the PID (Proportional-Integral-Derivative) control module, progressively minimizing the tracking error and ensuring the stability of the UAV formation configuration. Simulation results affirm the effectiveness and viability of the proposed formation control strategy elucidated in this article.