Multiple mobile agents with double integrator dynamics, following a leader to achieve a flocking motion formation, are studied in this paper. A class of local control laws for a group of mobile agents is proposed. Fro...Multiple mobile agents with double integrator dynamics, following a leader to achieve a flocking motion formation, are studied in this paper. A class of local control laws for a group of mobile agents is proposed. From a theoretical proof, the following conclusions are reached： （i） agents globally align their velocity vectors with a leader, （ii） they converge their velocities to the leaders velocity, （iii） collisions among interconnected agents are avoided, and （iv） agent＇s artificial potential functions are minimized. We model the interaction and/or communication relationship between agents by algebraic graph theory. Stability analysis is achieved by using classical Lyapunov theory in a fixed network topology, and differential inclusions and nonsmooth analysis in a switching network topology respectively. Simulation examples are provided.展开更多
An improved cooperative tracking model is proposed, which is based on the local information between mutually observable individuals with global object information, and this model is used for scalable social foraging s...An improved cooperative tracking model is proposed, which is based on the local information between mutually observable individuals with global object information, and this model is used for scalable social foraging swarm. In this model, the 'follower' individuals in the swarm take the center of the minimal circumcircle decided by the neighbors in the positive visual set of individual as its local object position. We study the stability properties of cooperative tracking behavior of social foraging swarm based on Lyapunov stability theory. Simulations show that the stable cooperative tracking behavior of the global social foraging swarm can be achieved easily, and beautiful scalability emerge from the proposed model for social foraging swarm.展开更多
In this article we specify an individual-based foraging swarm （i.e., group of agents） model with individuals that move in an n-dimensional multi-obstacle environment. The motion of each individual （i） is determine...In this article we specify an individual-based foraging swarm （i.e., group of agents） model with individuals that move in an n-dimensional multi-obstacle environment. The motion of each individual （i） is determined by three factors： i） attraction to the local object position （x^-io＋） which is decided by the local information about the individuals＇ position that individual i can find; ii） repulsion from the other individuals on short distances; and iii） attraction to the global object position （xgoal） or repulsion from the obstacles in the environment, The emergent behavior of the swarm motion is the result of a balance between inter-individual interaction and the simultaneous interactions of the swarm members with their environment. We study the stability properties of the collective behavior of the swarm based on Lyapunov stability theory. The simulations show that the swarm can converge to goal regions and diverge from obstacle regions of the environment while maintaining cohesive.展开更多
基金This work was supported in part by the NSFC (No.60274020) and the NSFC International Collaborative Project (No.60340420431).
文摘Multiple mobile agents with double integrator dynamics, following a leader to achieve a flocking motion formation, are studied in this paper. A class of local control laws for a group of mobile agents is proposed. From a theoretical proof, the following conclusions are reached： （i） agents globally align their velocity vectors with a leader, （ii） they converge their velocities to the leaders velocity, （iii） collisions among interconnected agents are avoided, and （iv） agent＇s artificial potential functions are minimized. We model the interaction and/or communication relationship between agents by algebraic graph theory. Stability analysis is achieved by using classical Lyapunov theory in a fixed network topology, and differential inclusions and nonsmooth analysis in a switching network topology respectively. Simulation examples are provided.
基金Supported by National Natural Science Foundation of P. R. China (60274014)
文摘An improved cooperative tracking model is proposed, which is based on the local information between mutually observable individuals with global object information, and this model is used for scalable social foraging swarm. In this model, the 'follower' individuals in the swarm take the center of the minimal circumcircle decided by the neighbors in the positive visual set of individual as its local object position. We study the stability properties of cooperative tracking behavior of social foraging swarm based on Lyapunov stability theory. Simulations show that the stable cooperative tracking behavior of the global social foraging swarm can be achieved easily, and beautiful scalability emerge from the proposed model for social foraging swarm.
基金This work was supported by the National Natural Science Foundation of China (No. 60574088).
文摘In this article we specify an individual-based foraging swarm （i.e., group of agents） model with individuals that move in an n-dimensional multi-obstacle environment. The motion of each individual （i） is determined by three factors： i） attraction to the local object position （x^-io＋） which is decided by the local information about the individuals＇ position that individual i can find; ii） repulsion from the other individuals on short distances; and iii） attraction to the global object position （xgoal） or repulsion from the obstacles in the environment, The emergent behavior of the swarm motion is the result of a balance between inter-individual interaction and the simultaneous interactions of the swarm members with their environment. We study the stability properties of the collective behavior of the swarm based on Lyapunov stability theory. The simulations show that the swarm can converge to goal regions and diverge from obstacle regions of the environment while maintaining cohesive.
