The pursuit-evasion problem is widespread in nature, engineering, and societal applications. It is commonly observed in nature that predators often exhibit faster speeds than their prey but have less agile maneuverability. Over millions of years of evolution, animals have developed effective and efficient strategies for pursuit and evasion. In this paper, we provide a dynamic framework for the pursuit-evasion problem of unicycle systems, drawing inspiration from nature. First, we address the scenario with one pursuer and one evader by proposing an Alert-Turn control strategy, which consists of two efficient ingredients: a sudden turning maneuver and an alert condition for starting and maintaining the maneuver. We present and analyze the escape and capture results at two levels: a lower level of a single run and a higher level with respect to parameters’ changes. In addition, we provide a theorem with sufficient conditions for capture. The Alert-Turn strategy is then extended to more complex scenarios involving multiple pursuers and evaders by integrating aggregation control laws and a target-changing mechanism. By adjusting a ‘selfish parameter’, the aggregation control commands produce various escape patterns of evaders: cooperative mode, selfish mode, and their combinations. The influence of the selfish parameter is quantified, and the target-changing mechanism is explored from a statistical perspective. Our findings align closely with observations in nature. Finally, the proposed strategies are validated through numerical simulations that replicate some chasing behaviors of animals in nature.

Efficient obstacle avoidance in Unmanned Aerial Vehicle (UAV) formations remains a significant challenge, particularly within dynamic and cluttered environments. While substantial advancements have been made in existing methods for formation control and obstacle avoidance, they frequently encounter constraints when segments of the UAV swarm become trapped in dead zones, which significantly degrade overall operational performance. To mitigate this issue, we propose a novel approach aimed at enhancing the swarm’s resilience by enabling UAVs to detect and proactively avoid potential dead zones. The proposed method constructs dynamic flight corridors by inflating the global trajectories of individual UAVs and systematically assessing their deviation from the primary formation path. This framework facilitates the early detection of potential dead zones, ensuring the swarm maintains both a safe and cohesive flight configuration. Extensive simulations across diverse environmental settings demonstrate the robustness and generalizability of the proposed method, underscoring its effectiveness in improving both formation stability and obstacle avoidance capabilities.

In this article, distributed optimal solutions are designed for networked multiagent pursuit-evasion (MPE) games for capture and formation control. In the games, the pursuers aim to minimize the distance from their target evaders while the evaders attempt to maximize it, and at the same time, all the players desire to maintain cohesion with their teammates. The goals of agents are obviously reflected in the obtained optimal control strategies, which consist of an attracting term and/or a repelling term. Nash equilibrium is obtained by means of optimal strategies using the solutions of the Hamilton-Jacobi-Isaacs equations. Furthermore, three scenarios are considered in the MPE game: one-pursuer one-evader, multiple-pursuer one-evader, and multiple-pursuer multiple-evader, where sufficient conditions are given for pursuers in achieving exponential capture or formation control with ultimate zero or bounded errors. It is shown that the conditions depend on the structure of the communication graph, the parameters in the controllers, and the expected formation configurations. Finally, both simulations and real flight experiments successfully demonstrate the effectiveness of the proposed strategies.

This paper presents decentralized solutions for addressing pursuit-evasion problems involving high-order in-tegrators with intracoalition cooperation and intercoalition confrontation. To ensure that the control strategies indepen-dent of the relative velocities, accelerations and higher order information of neighbors, we introduce distinct error vari-ables and hyper-variables. Consequently, this approach only requires agents to exchange position information or measure the relative positions of neighbors. The distributed strategies reflect the goals of intracoalition cooperation or intercoalition confrontation of the players. Additionally, we present the conditions for capture and formation control with exponential convergence for three cases: one-pursuer-one-evader, multiple-pursuer-one-evader, and multiple- pursuer- multiple-evader. The results show that the conditions depend on the structure of the communication graph, the weights in the control law, and the expected formation configuration. Finally, the effectiveness of the proposed algorithm is demonstrated through simulation results.

This paper presents decentralized solutions for pursuit-evasion problems involving high-order integrators with intracoalition cooperation and intercoalition confrontation. Distinct error variables and hyper-variables are introduced to ensure the control strategies to be independent of the relative velocities, accelerations and higher order information of neighbors. Consequently, our approach only requires agents to exchange position information or to measure the relative positions of the neighbors. The distributed strategies take into consideration the goals of intracoalition cooperation or intercoalition confrontation of the players. Furthermore, after establishing a sufficient and necessary condition for a class of high-order integrators, we present conditions for capture and formation control with exponential convergence for three scenarios: one-pursuer-one-evader, multiple-pursuer-one-evader, and multiple-pursuer-multiple-evader. It is shown that the conditions depend on the structure of the communication graph, the weights in the control law, and the expected formation configuration. Finally, the effectiveness of the proposed algorithm is demonstrated through simulation results.

This paper proposes an adaptive observer for an active leader and designed a distributed observer-based control law for the formation control of networked uncertain offshore vessels under the switching topologies. The design of the observer, only depending on the output of the leader system, is featured with the ability of accurately estimating the output of the leader system with an unknown input over the time-varying communication network, satisfying the periodic switching condition. Then based on the output-based observer, the formation problem of multiple offshore vessels is converted into the stabilization problem of a multi-input multi-output augmented system by further combining the internal model technique and performing a coordinate and input transformation. The original problem is finally solved through constructing a stabilizer for the time-varying uncertain augmented system, and the efficiency of our design is validated by the formation control of a group of offshore vessels.

In this paper, distributed optimal solutions are designed for networked multiagent pursuit-evasion (MPE) games for capture and formation control. In the games, the pursuers aim to minimize the distance from their target evaders while the evaders attempt to maximize it, and at the same time, all players desire to maintain cohesion with their teammates. The goals of agents are obviously reflected in the obtained optimal control strategies which consist of an attracting term and/or a repelling term. Nash equilibrium is obtained by means of optimal strategies using the solutions of the HJI equations. Furthermore, three scenarios are considered in the MPE game: one-pursuer-one-evader, multiple-pursuer-one-evader, and multiple-pursuer-multiple-evader, where sufficient conditions are given for pursuers in achieving capture or formation control with ultimate zero or bounded errors. It is shown that the conditions depend on the structure of the communication graph, the parameters in the controllers, and the expected formation configurations. Finally, both simulations and real flight experiments successfully demonstrate the effectiveness of the proposed strategies.