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20162022
most citedOnline Photometric Calibration of Automatic Gain Thermal Infrared Cameras

18 citations · 19 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.RO20221 cited

Lunar Rover Localization Using Craters as Landmarks

Larry Matthies, Shreyansh Daftry, Scott Tepsuporn +5

Onboard localization capabilities for planetary rovers to date have used relative navigation, by integrating combinations of wheel odometry, visual odometry, and inertial measureme…

cs.RO2022

MLNav: Learning to Safely Navigate on Martian Terrains

Shreyansh Daftry, Neil Abcouwer, Tyler Del Sesto +7

We present MLNav, a learning-enhanced path planning framework for safety-critical and resource-limited systems operating in complex environments, such as rovers navigating on Mars.…

cs.RO2021

Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching

Tu-Hoa Pham, William Seto, Shreyansh Daftry +11

We consider the problem of rover relocalization in the context of the notional Mars Sample Return campaign. In this campaign, a rover (R1) needs to be capable of autonomously navig…

cs.RO2021

NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge

Ali Agha, Kyohei Otsu, Benjamin Morrell +69

This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARP…

cs.RO2018

Online Self-supervised Scene Segmentation for Micro Aerial Vehicles

Shreyansh Daftry, Yashasvi Agrawal, Larry Matthies

Recently, there have been numerous advances in the development of payload and power constrained lightweight Micro Aerial Vehicles (MAVs). As these robots aspire for high-speed auto…

cs.RO2016

Robust Monocular Flight in Cluttered Outdoor Environments

Shreyansh Daftry, Sam Zeng, Arbaaz Khan +4

Recently, there have been numerous advances in the development of biologically inspired lightweight Micro Aerial Vehicles (MAVs). While autonomous navigation is fairly straight-for…