We propose a new algorithm to simplify the controller development for distributed robotic systems subject to external observations, disturbances, and communication delays. Unlike prior approaches that propose specialized solutions to handling communication latency for specific robotic applications, our algorithm uses an arbitrary centralized controller as the specification and automatically generates distributed controllers with communication management and delay compensation. We formulate our goal as nonlinear optimal control -- using a regret minimizing objective that measures how much the distributed agents behave differently from the delay-free centralized response -- and solve for optimal actions w.r.t. local estimations of this objective using gradient-based optimization. We analyze our proposed algorithm's behavior under a linear time-invariant special case and prove that the closed-loop dynamics satisfy a form of input-to-state stability w.r.t. unexpected disturbances and observations. Our experimental results on both simulated and real-world robotic tasks demonstrate the practical usefulness of our approach and show significant improvement over several baseline approaches.
翻译:我们提出一个新的算法,以简化受外部观察、干扰和通信延误影响的分布式机器人系统的控制器开发。与以前提出处理特定机器人应用通信潜伏的专门解决办法的做法不同,我们的算法使用任意的中央控制器作为规格,并自动生成分布式控制器,进行通信管理和延迟补偿。我们把目标设计为非线性最佳控制 -- -- 利用一个最小化目标,即测量分布式代理器的行为与无延迟集中反应的不同程度 -- -- 并用梯度优化办法解决当地对这一目标的最佳估计。我们分析了我们提议的算法在线性时间变化特例下的行为,并证明闭环动态满足了一种输入到状态的稳定性的意外扰动和观察形式。我们在模拟和现实世界机器人任务方面的实验结果显示了我们的方法的实际效用,并展示了在几个基线方法上的重大改进。