5 citations · 5 across the 3 of their papers we have counts for
7 papers · 1 filter
Multimodal dynamics modeling for off-road autonomous vehicles
Jean-François Tremblay, Travis Manderson, Aurélio Noca +2
Dynamics modeling in outdoor and unstructured environments is difficult because different elements in the environment interact with the robot in ways that can be hard to predict. L…
Vision-Based Goal-Conditioned Policies for Underwater Navigation in the Presence of Obstacles
Travis Manderson, Juan Camilo Gamboa Higuera, Stefan Wapnick +4
We present Nav2Goal, a data-efficient and end-to-end learning method for goal-conditioned visual navigation. Our technique is used to train a navigation policy that enables a robot…
Learning to Drive Off Road on Smooth Terrain in Unstructured Environments Using an On-Board Camera and Sparse Aerial Images
Travis Manderson, Stefan Wapnick, David Meger +1
We present a method for learning to drive on smooth terrain while simultaneously avoiding collisions in challenging off-road and unstructured outdoor environments using only visual…
One-Shot Informed Robotic Visual Search in the Wild
Karim Koreitem, Florian Shkurti, Travis Manderson +3
We consider the task of underwater robot navigation for the purpose of collecting scientifically relevant video data for environmental monitoring. The majority of field robots that…
DeepURL: Deep Pose Estimation Framework for Underwater Relative Localization
Bharat Joshi, Md Modasshir, Travis Manderson +5
In this paper, we propose a real-time deep learning approach for determining the 6D relative pose of Autonomous Underwater Vehicles (AUV) from a single image. A team of autonomous…
Heterogeneous Robot Teams for Informative Sampling
Travis Manderson, Sandeep Manjanna, Gregory Dudek
In this paper we present a cooperative multi-robot strategy to adaptively explore and sample environments that are unfavorable for humans. We propose a methodology for a team of he…