This paper presents a new online multi-agent trajectory planning algorithm that guarantees to generate safe, dynamically feasible trajectories in a cluttered environment. The proposed algorithm utilizes a linear safe corridor (LSC) to formulate the distributed trajectory optimization problem with only feasible constraints, so it does not resort to slack variables or soft constraints to avoid optimization failure. Also, we adopt a priority-based goal planning method to prevent the deadlock without additional communication for decision making. The proposed algorithm can compute the trajectories for 60 agents on average 15.5 ms per agent with an Intel i7 laptop and can find the trajectory that reaches the goal without deadlock in both random forest and indoor space. We validated safety and operability of the proposed algorithm through a real flight test with ten quadrotors in a maze-like environment.
翻译:本文介绍了一个新的在线多试剂轨迹规划算法,该算法保证在一个四分五裂的环境中产生安全、动态可行的轨道。提议的算法利用线性安全走廊(LSC)来提出分布式轨迹优化问题,但只有可行的限制,因此它不会采用松懈的变数或软性限制来避免优化失败。此外,我们还采用了基于优先事项的目标规划方法,以防止僵局,而不必为决策提供更多的沟通。提议的算法可以计算60个试剂的轨迹,平均每个试剂15.5毫秒,使用英特尔i7笔笔记本,并找到在随机森林和室内空间都能够不陷入僵局地达到目标的轨迹。我们通过在类似于迷宫的环境中对十个四重体进行真正的飞行试验,验证了拟议算法的安全和可操作性。