202 citations · 323 across the 7 of their papers we have counts for
8 papers
DSOL: A Fast Direct Sparse Odometry Scheme
Chao Qu, Shreyas S. Shivakumar, Ian D. Miller +1
In this paper, we describe Direct Sparse Odometry Lite (DSOL), an improved version of Direct Sparse Odometry (DSO). We propose several algorithmic and implementation enhancements w…
LLOL: Low-Latency Odometry for Spinning Lidars
Chao Qu, Shreyas S. Shivakumar, Wenxin Liu +1
In this paper, we present a low-latency odometry system designed for spinning lidars. Many existing lidar odometry methods wait for an entire sweep from the lidar before processing…
Large-scale Autonomous Flight with Real-time Semantic SLAM under Dense Forest Canopy
Xu Liu, Guilherme V. Nardari, Fernando Cladera Ojeda +8
Semantic maps represent the environment using a set of semantically meaningful objects. This representation is storage-efficient, less ambiguous, and more informative, thus facilit…
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty
Chao Qu, Wenxin Liu, Camillo J. Taylor
In this work we investigate the problem of uncertainty estimation for image-guided depth completion. We extend Deep Basis Fitting (DBF) for depth completion within a Bayesian evide…
SLOAM: Semantic Lidar Odometry and Mapping for Forest Inventory
Steven W. Chen, Guilherme V. Nardari, Elijah S. Lee +4
This paper describes an end-to-end pipeline for tree diameter estimation based on semantic segmentation and lidar odometry and mapping. Accurate mapping of this type of environment…
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…