We present a method for optimal coordination of multiple vehicle teams when multiple endpoint configurations are equally desirable, such as seen in the autonomous assembly of formation flight. The individual vehicles' positions in the formation are not assigned a priori and a key challenge is to find the optimal configuration assignment along with the optimal control and trajectory. Commonly, assignment and trajectory planning problems are solved separately. We introduce a new multi-vehicle coordination paradigm, where the optimal goal assignment and optimal vehicle trajectories are found simultaneously from a viscosity solution of a single Hamilton-Jacobi (HJ) partial differential equation (PDE), which provides a necessary and sufficient condition for global optimality. Intrinsic in this approach is that individual vehicle dynamic models need not be the same, and therefore can be applied to heterogeneous systems. Numerical methods to solve the HJ equation have historically relied on a discrete grid of the solution space and exhibits exponential scaling with system dimension, preventing their applicability to multiple vehicle systems. By utilizing a generalization of the Hopf formula, we avoid the use of grids and present a method that exhibits polynomial scaling in the number of vehicles.
翻译:在多端配置同样可取的情况下,我们为多车辆队提供了最佳协调方法,例如,在编队飞行的自主组合中可以看到的多端配置;在编队中的各车辆位置没有事先分配,关键挑战是找到最佳配置任务以及最佳控制和轨迹;通常,任务分配和轨迹规划问题将分别解决;我们采用新的多车辆协调模式,从单一汉密尔顿-贾科比(HJ)部分差异方程式(PDE)的粘度解决方案中同时找到最佳目标分配和最佳车辆轨迹,该方程式为全球最佳性提供了必要和充分的条件;这种方法的内在性是,单个车辆动态模式不需要相同,因此可以适用于多式系统;解决HJ方程式的数值方法历来依赖于离散的解决方案空间网格,并展示具有系统层面的指数缩放,防止其对多车辆系统的适用性;我们通过对Hopf公式的笼统化,避免使用电网格,并提出一种在车辆数量上显示多式比例的方法。