M
Michael R. Benjamin
Researcher at Massachusetts Institute of Technology
Publications - 59
Citations - 1579
Michael R. Benjamin is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Collision avoidance & Remotely operated underwater vehicle. The author has an hindex of 18, co-authored 56 publications receiving 1338 citations. Previous affiliations of Michael R. Benjamin include Naval Sea Systems Command & Brown University.
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Journal ArticleDOI
Nested Autonomy for Unmanned Marine Vehicles with MOOS-IvP
TL;DR: The IvP Helm is the primary component of an additional set of capabilities implemented to form a full marine autonomy suite known as MOOS‐IvP, and this software and architecture are platform and mission agnostic.
Proceedings ArticleDOI
Duckietown: An open, inexpensive and flexible platform for autonomy education and research
Liam Paull,Jacopo Tani,Heejin Ahn,Javier Alonso-Mora,Luca Carlone,Michal Cap,Yu Fan Chen,Changhyun Choi,Jeff Dusek,Yajun Fang,Daniel Hoehener,Shih-Yuan Liu,Michael Novitzky,Igor Franzoni Okuyama,Jason Pazis,Guy Rosman,Valerio Varricchio,Hsueh-Cheng Wang,Dmitry S. Yershov,Hang Zhao,Michael R. Benjamin,Christopher E. Carr,Maria T. Zuber,Sertac Karaman,Emilio Frazzoli,Domitilla Del Vecchio,Daniela Rus,Jonathan P. How,John J. Leonard,Andrea Censi +29 more
TL;DR: Duckietown is an open, inexpensive and flexible platform for autonomy education and research that comprises small autonomous vehicles built from off-the-shelf components, and cities complete with roads, signage, traffic lights, obstacles, and citizens in need of transportation.
Journal ArticleDOI
A method for protocol‐based collision avoidance between autonomous marine surface craft
TL;DR: This work represents the first in‐field demonstration of multiobjective optimization applied to autonomous COLREGS‐based marine vehicle navigation, and presents experimental validation of this approach using multiple autonomous surface craft.
Proceedings ArticleDOI
Navigation of unmanned marine vehicles in accordance with the rules of the road
TL;DR: This work represents the first in-field demonstration of multiobjective optimization applied to autonomous COLREGS-based marine vehicle navigation, and presents experimental validation of this approach using multiple autonomous surface craft.
An Overview of MOOS-IvP and a Brief Users Guide to the IvP Helm Autonomy Software
TL;DR: This document describes the configuration and use of the IvP Helm, provides examples of simple missions and information on how to download and build the software from the MOOS-IvP server at www.moosivp.org.