activity
20222024
most citedPresent and Future of SLAM in Extreme Underground Environments

38 citations · 73 across the 21 of their papers we have counts for

collaborators

21 papers

cs.CV20241 cited

FIReStereo: Forest InfraRed Stereo Dataset for UAS Depth Perception in Visually Degraded Environments

Devansh Dhrafani, Yifei Liu, Andrew Jong +6

Robust depth perception in visually-degraded environments is crucial for autonomous aerial systems. Thermal imaging cameras, which capture infrared radiation, are robust to visual…

cs.RO20242 cited

Fast and Modular Autonomy Software for Autonomous Racing Vehicles

Andrew Saba, Aderotimi Adetunji, Adam Johnson +27

Autonomous motorsports aim to replicate the human racecar driver with software and sensors. As in traditional motorsports, Autonomous Racing Vehicles (ARVs) are pushed to their han…

cs.RO2024

UNRealNet: Learning Uncertainty-Aware Navigation Features from High-Fidelity Scans of Real Environments

Samuel Triest, David D. Fan, Sebastian Scherer +1

Traversability estimation in rugged, unstructured environments remains a challenging problem in field robotics. Often, the need for precise, accurate traversability estimation is i…

cs.CV2024

AirShot: Efficient Few-Shot Detection for Autonomous Exploration

Zihan Wang, Bowen Li, Chen Wang +1

Few-shot object detection has drawn increasing attention in the field of robotic exploration, where robots are required to find unseen objects with a few online provided examples.…

eess.SY20243 cited

A Unified MPC Strategy for a Tilt-rotor VTOL UAV Towards Seamless Mode Transitioning

Qizhao Chen, Ziqi Hu, Junyi Geng +3

Capabilities of long-range flight and vertical take-off and landing (VTOL) are essential for Urban Air Mobility (UAM). Tiltrotor VTOLs have the advantage of balancing control simpl…

cs.RO2024

TartanDrive 2.0: More Modalities and Better Infrastructure to Further Self-Supervised Learning Research in Off-Road Driving Tasks

Matthew Sivaprakasam, Parv Maheshwari, Mateo Guaman Castro +6

We present TartanDrive 2.0, a large-scale off-road driving dataset for self-supervised learning tasks. In 2021 we released TartanDrive 1.0, which is one of the largest datasets for…