We consider the problem of autonomous navigation using limited information from a remote sensor network. Because the remote sensors are power and bandwidth limited, we use event-triggered (ET) estimation to manage communication costs. We introduce a fast and efficient sampling-based planner which computes motion plans coupled with ET communication strategies that minimize communication costs, while satisfying constraints on the probability of reaching the goal region and the point-wise probability of collision. We derive a novel method for offline propagation of the expected state distribution, and corresponding bounds on this distribution. These bounds are used to evaluate the chance constraints in the algorithm. Case studies establish the validity of our approach, demonstrating fast computation of optimal plans.

翻译：我们研究了利用远程传感器网络的有限信息进行自主导航的问题。由于远程传感器的功率和带宽有限，我们采用事件触发（ET）估计来管理通信成本。我们提出了一种快速高效的基于采样的规划器，该规划器能够计算与ET通信策略相结合的运动规划，从而在满足到达目标区域的概率约束和点态碰撞概率约束的同时最小化通信成本。我们推导了一种新的离线传播期望状态分布及其相应边界的方法。这些边界用于评估算法中的机会约束。案例研究验证了我们方法的有效性，展示了最优规划的快速计算能力。