202 citations · 552 across the 26 of their papers we have counts for
7 papers · 1 filter
Depth Completion via Deep Basis Fitting
Chao Qu, Ty Nguyen, Camillo J. Taylor
In this paper we consider the task of image-guided depth completion where our system must infer the depth at every pixel of an input image based on the image content and a sparse s…
PST900: RGB-Thermal Calibration, Dataset and Segmentation Network
Shreyas S. Shivakumar, Neil Rodrigues, Alex Zhou +3
In this work we propose long wave infrared (LWIR) imagery as a viable supporting modality for semantic segmentation using learning-based techniques. We first address the problem of…
Mine Tunnel Exploration using Multiple Quadrupedal Robots
Ian D. Miller, Fernando Cladera, Anthony Cowley +11
Robotic exploration of underground environments is a particularly challenging problem due to communication, endurance, and traversability constraints which necessitate high degrees…
Vision-based Multi-MAV Localization with Anonymous Relative Measurements Using Coupled Probabilistic Data Association Filter
Ty Nguyen, Kartik Mohta, Camillo J. Taylor +1
We address the localization of robots in a multi-MAV system where external infrastructure like GPS or motion capture systems may not be available. Our approach lends itself to impl…
MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based Tasks
Ty Nguyen, Shreyas S. Shivakumar, Ian D. Miller +9
Real-time semantic image segmentation on platforms subject to size, weight and power (SWaP) constraints is a key area of interest for air surveillance and inspection. In this work,…
DFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance
Yilun Zhang, Ty Nguyen, Ian D. Miller +4
Depth estimation is an important capability for autonomous vehicles to understand and reconstruct 3D environments as well as avoid obstacles during the execution. Accurate depth se…
DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth Completion
Shreyas S. Shivakumar, Ty Nguyen, Ian D. Miller +3
In this paper we propose a convolutional neural network that is designed to upsample a series of sparse range measurements based on the contextual cues gleaned from a high resoluti…