16 citations · 19 across the 5 of their papers we have counts for
5 papers
A Survey on the Integration of Machine Learning with Sampling-based Motion Planning
Troy McMahon, Aravind Sivaramakrishnan, Edgar Granados +1
Sampling-based methods are widely adopted solutions for robot motion planning. The methods are straightforward to implement, effective in practice for many robotic systems. It is o…
The effect of cities and distance on COVID-19 spreading in the United States
Troy McMahon, Shlomo Havlin, Lazaros K. Gallos
The COVID-19 pandemic has evolved over time through multiple spatial and temporal dynamics. The varying extent of interactions among different geographical areas can result to a co…
Data-Efficient Learning of High-Quality Controls for Kinodynamic Planning used in Vehicular Navigation
Seth Karten, Aravind Sivaramakrishnan, Edgar Granados +2
This paper aims to improve the path quality and computational efficiency of kinodynamic planners used for vehicular systems. It proposes a learning framework for identifying promis…
Improving Kinodynamic Planners for Vehicular Navigation with Learned Goal-Reaching Controllers
Aravind Sivaramakrishnan, Edgar Granados, Seth Karten +2
This paper aims to improve the path quality and computational efficiency of sampling-based kinodynamic planners for vehicular navigation. It proposes a learning framework for ident…
Spatial correlations in geographical spreading of COVID-19 in USA
Troy McMahon, Adrian Chan, Shlomo Havlin +1
The global spread of the COVID-19 pandemic has followed complex pathways, largely attributed to the high virus infectivity, human travel patterns, and the implementation of multipl…