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Using Synthetic Data and Deep Networks to Recognize Primitive Shapes for Object Grasping
Yunzhi Lin, Chao Tang, Fu-Jen Chu +1
A segmentation-based architecture is proposed to decompose objects into multiple primitive shapes from monocular depth input for robotic manipulation. The backbone deep network is…
Robust Monocular Edge Visual Odometry through Coarse-to-Fine Data Association
Xiaolong Wu, Patricio Vela, Cedric Pradalier
In this work, we propose a monocular visual odometry framework, which allows exploiting the best attributes of edge feature for illumination-robust camera tracking, while at the sa…
Recognizing Object Affordances to Support Scene Reasoning for Manipulation Tasks
Fu-Jen Chu, Ruinian Xu, Chao Tang +1
Affordance information about a scene provides important clues as to what actions may be executed in pursuit of meeting a specified goal state. Thus, integrating affordance-based re…
Autonomous, Monocular, Vision-Based Snake Robot Navigation and Traversal of Cluttered Environments using Rectilinear Gait Motion
Alexander H. Chang, Shiyu Feng, Yipu Zhao +2
Rectilinear forms of snake-like robotic locomotion are anticipated to be an advantage in obstacle-strewn scenarios characterizing urban disaster zones, subterranean collapses, and…
Characterizing SLAM Benchmarks and Methods for the Robust Perception Age
Wenkai Ye, Yipu Zhao, Patricio A. Vela
The diversity of SLAM benchmarks affords extensive testing of SLAM algorithms to understand their performance, individually or in relative terms. The ad-hoc creation of these bench…
Good Feature Selection for Least Squares Pose Optimization in VO/VSLAM
Yipu Zhao, Patricio A. Vela
This paper aims to select features that contribute most to the pose estimation in VO/VSLAM. Unlike existing feature selection works that are focused on efficiency only, our method…