基于势场函数的多智能体编队避障控制

势场函数方法广泛应用在避障与目标追击控制中,但是大多应用在静态环境中,即障碍物与目标是静止的。通过扩展势场函数,并结合图论与领航者方法,设计出新的控制算法。障碍物与目标的速度都考虑在势场函数定义中。基于这种新的控制算法,研究了多智能体群集控制,所提方法不仅保证智能体追击上运动的目标,同时确保能安全躲避障碍。由于所提方法是基于智能体行为,因此方法的一个优点就是容易升级。最后,仿真表明所提方法的有效性。

Potential Function Based Control for Obstacle Avoidance in Formation of Multiple Agents

Potential function method has been widely used in obstacle avoidance and target tracking of multiple agents,but mostly in static environment where the obstacles and target are stationary.Potential function is extend,and a new control algorithm is designed together with graph theory and leader-follower method.The velocities of both obstacles and target are also included in the definition of the potential function.Furthermore,based on a new control strategy,the problem of multiple agents flocking is investigated.The proposed method guarantees the agents not only track given moving target while maintaining the formation,but also avoid moving obstacles.One of advantages of the proposed method is that it is easy scalable because control is based on general rule that determines behaviors of all agents.Finally,simulation studies are provided to verify the effectiveness of the proposed method.