  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.

Robotics