6 citations · 8 across the 6 of their papers we have counts for
6 papers
Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation
Tyler Han, Bat Nemekhbold, Siyang Shen +6
Current methods in robot learning are fundamentally bottlenecked by one or more of: hand-designed rewards, simulation modeling, or action supervision (e.g. teleoperation) each requ…
Long Range Navigator (LRN): Extending robot planning horizons beyond metric maps
Matt Schmittle, Rohan Baijal, Nathan Hatch +6
A robot navigating an outdoor environment with no prior knowledge of the space must rely on its local sensing to perceive its surroundings and plan. This can come in the form of a…
Multi-Sample Long Range Path Planning under Sensing Uncertainty for Off-Road Autonomous Driving
Matt Schmittle, Rohan Baijal, Brian Hou +2
We focus on the problem of long-range dynamic replanning for off-road autonomous vehicles, where a robot plans paths through a previously unobserved environment while continuously…
SoRTS: Learned Tree Search for Long Horizon Social Robot Navigation
Ingrid Navarro, Jay Patrikar, Joao P. A. Dantas +4
The fast-growing demand for fully autonomous robots in shared spaces calls for the development of trustworthy agents that can safely and seamlessly navigate in crowded environments…
Learned Tree Search for Long-Horizon Social Robot Navigation in Shared Airspace
Ingrid Navarro, Jay Patrikar, Joao P. A. Dantas +4
The fast-growing demand for fully autonomous aerial operations in shared spaces necessitates developing trustworthy agents that can safely and seamlessly navigate in crowded, dynam…
Challenges in Close-Proximity Safe and Seamless Operation of Manned and Unmanned Aircraft in Shared Airspace
Jay Patrikar, Joao P. A. Dantas, Sourish Ghosh +11
We propose developing an integrated system to keep autonomous unmanned aircraft safely separated and behave as expected in conjunction with manned traffic. The main goal is to achi…