基于模型预测控制的无人车编队避障方法

Formation Obstacle Avoidance Based on Model Predictive Control for Unmanned Vehicles

  • 摘要: 为研究障碍物环境下基于模型预测控制的无人车编队避障方法,建立了包含虚拟智能体状态的编队避障函数,使避障问题容易用优化方法求解. 在无人车编队内部引入优先级策略实现编队内部避碰,并通过动态事件触发机制减小无人车之间通讯带宽占用. 对该方法进行了计算机仿真验证,在给定多边形障碍物环境下,使用领导者−追随者架构执行编队行驶任务,并借助事件触发器实现间歇通讯. 结果表明,相较于传统方法,所设计的编队控制器能够提高带宽约束下无人车编队行驶安全性.

     

    Abstract: An obstacle avoidance method was proposed based on model predictive control for unmanned vehicle formation. Firstly, a formation obstacle avoidance function including the virtual agent state was established to make the obstacle avoidance problem been solved suitably with the optimizer. And a priority strategy was introduced to realize collision avoidance in unmanned vehicle formation. Then, a dynamic event triggering mechanism was introduced to reduce the bandwidth usage of communication between unmanned vehicles. Finally, simulation tests were carried out to evaluate the performance of the designed controller, conducting the formation driving tasks based on a leader-tracker architecture under the environment of given polygonal obstacles, and realizing the intermittent communication during driving with the help of event trigger. The results show that compared with traditional methods, the designed formation controller can realize the collision-free driving with limited bandwidth for unmanned vehicle formation.

     

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