Title
Topology-Aware Self-Organizing Maps for Robotic Information Gathering
Abstract
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 distinct classes of trajectories, each of which has improved convexity compared with the original function. We then leverage a Stochastic Gradient Ascent (SGA) optimization algorithm within each of these classes to optimize promising representative paths. The increased convexity leads to an improved chance of SGA finding the globally optimal path across all homotopy classes. We demonstrate our approach in three different simulated experiments. First, we show that our SOM is able to correctly learn the topological features of a gyre environment with a well-defined topology. Then, in the second set of experiments, we compare the effectiveness of our algorithm in an information gathering task across the gyre world, a set of randomly generated worlds, and a set of worlds drawn from real-world ocean model data. In these experiments our algorithm performs competitively or better than a state-of-the-art Branch and Bound while requiring significantly less computation time. Lastly, the final set of experiments show that our method scales better than the comparison methods across different planning mission sizes in real-world environments.
Year
DOI
Venue
2020
10.1109/IROS45743.2020.9341040
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Keywords
DocType
ISSN
real-world ocean model data,real-world environments,robotic information gathering,maximally informative path,SOM,topological features,information function,globally optimal path,homotopy classes,stochastic gradient ascent optimization,topology-aware self-organizing maps,SGA,autonomous robots
Conference
2153-0858
ISBN
Citations 
PageRank 
978-1-7281-6213-3
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Seth McCammon102.37
Dylan Jones200.68
Geoffrey A. Hollinger333427.61