no code implementations • 19 May 2022 • Wei-Di Chang, Juan Camilo Gamboa Higuera, Scott Fujimoto, David Meger, Gregory Dudek
We present an algorithm for Inverse Reinforcement Learning (IRL) from expert state observations only.
1 code implementation • 22 Mar 2020 • Karim Koreitem, Florian Shkurti, Travis Manderson, Wei-Di Chang, Juan Camilo Gamboa Higuera, Gregory Dudek
In this paper we propose a method that enables informed visual navigation via a learned visual similarity operator that guides the robot's visual search towards parts of the scene that look like an exemplar image, which is given by the user as a high-level specification for data collection.
1 code implementation • 17 Sep 2019 • Wei Jiang, Juan Camilo Gamboa Higuera, Baptiste Angles, Weiwei Sun, Mehrsan Javan, Kwang Moo Yi
We propose an optimization-based framework to register sports field templates onto broadcast videos.
no code implementations • 2 Jun 2019 • Melissa Mozifian, Juan Camilo Gamboa Higuera, David Meger, Gregory Dudek
We explore the use of gradient-based search methods to learn a domain randomization with the following properties: 1) The trained policy should be successful in environments sampled from the domain randomization distribution 2) The domain randomization distribution should be wide enough so that the experience similar to the target robot system is observed during training, while addressing the practicality of training finite capacity models.
1 code implementation • 13 Mar 2019 • Sanjay Thakur, Herke van Hoof, Juan Camilo Gamboa Higuera, Doina Precup, David Meger
Learned controllers such as neural networks typically do not have a notion of uncertainty that allows to diagnose an offset between training and testing conditions, and potentially intervene.
3 code implementations • 6 Mar 2018 • Juan Camilo Gamboa Higuera, David Meger, Gregory Dudek
Finally, we assess the performance of the algorithm for learning motor controllers for a six legged autonomous underwater vehicle.
Model-based Reinforcement Learning
reinforcement-learning
+2
1 code implementation • 25 Sep 2017 • Florian Shkurti, Wei-Di Chang, Peter Henderson, Md Jahidul Islam, Juan Camilo Gamboa Higuera, Jimmy Li, Travis Manderson, Anqi Xu, Gregory Dudek, Junaed Sattar
We present a robust multi-robot convoying approach that relies on visual detection of the leading agent, thus enabling target following in unstructured 3-D environments.