1 code implementation • 22 Mar 2022 • Mateus Valverde Gasparino, Arun Narenthiran Sivakumar, Yixiao Liu, Andres Eduardo Baquero Velasquez, Vitor Akihiro Hisano Higuti, John Rogers, Huy Tran, Girish Chowdhary
We present a self-supervised approach for learning to predict traversable paths for wheeled mobile robots that require good traction to navigate.
no code implementations • 17 Mar 2022 • Derrik E. Asher, Anjon Basak, Rolando Fernandez, Piyush K. Sharma, Erin G. Zaroukian, Christopher D. Hsu, Michael R. Dorothy, Thomas Mahre, Gerardo Galindo, Luke Frerichs, John Rogers, John Fossaceca
Reinforcement learning (RL) approaches can illuminate emergent behaviors that facilitate coordination across teams of agents as part of a multi-agent system (MAS), which can provide windows of opportunity in various military tasks.
1 code implementation • 11 Feb 2017 • Siddharth Choudhary, Luca Carlone, Carlos Nieto, John Rogers, Henrik I. Christensen, Frank Dellaert
Our field tests show that the combined use of our distributed algorithms and object-based models reduces the communication requirements by several orders of magnitude and enables distributed mapping with large teams of robots in real-world problems.