4 papers
Learning to Explore Indoor Environments using Autonomous Micro Aerial Vehicles
Yuezhan Tao, Eran Iceland, Beiming Li +7
In this paper, we address the challenge of exploring unknown indoor aerial environments using autonomous aerial robots with Size Weight and Power (SWaP) constraints. The SWaP const…
Place Recognition in Forests with Urquhart Tessellations
Guilherme V. Nardari, Avraham Cohen, Steven W. Chen +4
In this letter, we present a novel descriptor based on Urquhart tessellations derived from the position of trees in a forest. We propose a framework that uses these descriptors to…
PennSyn2Real: Training Object Recognition Models without Human Labeling
Ty Nguyen, Ian D. Miller, Avi Cohen +5
Scalable training data generation is a critical problem in deep learning. We propose PennSyn2Real - a photo-realistic synthetic dataset consisting of more than 100,000 4K images of…
Mine Tunnel Exploration using Multiple Quadrupedal Robots
Ian D. Miller, Fernando Cladera, Anthony Cowley +11
Robotic exploration of underground environments is a particularly challenging problem due to communication, endurance, and traversability constraints which necessitate high degrees…