7 citations · 12 across the 3 of their papers we have counts for
4 papers · 1 filter
NavTuner: Learning a Scene-Sensitive Family of Navigation Policies
Haoxin Ma, Justin S. Smith, Patricio A. Vela
The advent of deep learning has inspired research into end-to-end learning for a variety of problem domains in robotics. For navigation, the resulting methods may not have the gene…
Closed-Loop Benchmarking of Stereo Visual-Inertial SLAM Systems: Understanding the Impact of Drift and Latency on Tracking Accuracy
Yipu Zhao, Justin S. Smith, Sambhu H. Karumanchi +1
Visual-inertial SLAM is essential for robot navigation in GPS-denied environments, e.g. indoor, underground. Conventionally, the performance of visual-inertial SLAM is evaluated wi…
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…
Learning to Navigate: Exploiting Deep Networks to Inform Sample-Based Planning During Vision-Based Navigation
Justin S. Smith, Jin-Ha Hwang, Fu-Jen Chu +1
Recent applications of deep learning to navigation have generated end-to-end navigation solutions whereby visual sensor input is mapped to control signals or to motion primitives.…