3 accepted papers
In this paper, we present a novel algorithm for constructing a maximally informative path for a robot in an information gathering task. We use a Self-Organizing Map (SOM) framework to discover important topological features in the information function. Using these features, we identify a set of dist…
In this work, we present a Stochastic Gradient Ascent (SGA) algorithm for multi-vehicle information gathering that accounts for limitations on a vehicle's control authority caused by external forces. By representing vehicle paths using a novel action space representation, rather than a state space r…
We present a framework for planning energy-efficient trajectories through strong and uncertain disturbances, such as ocean currents and wind fields. First, we develop an iterative optimization algorithm for path planning. The algorithm samples smoothly deformed paths around the current best path est