1 citations · 1 across the 2 of their papers we have counts for
6 papers
Out-of-Distribution Robustness with Deep Recursive Filters
Kapil D. Katyal, I-Jeng Wang, Gregory D. Hager
Accurate state and uncertainty estimation is imperative for mobile robots and self driving vehicles to achieve safe navigation in pedestrian rich environments. A critical component…
High-Speed Robot Navigation using Predicted Occupancy Maps
Kapil D. Katyal, Adam Polevoy, Joseph Moore +2
Safe and high-speed navigation is a key enabling capability for real world deployment of robotic systems. A significant limitation of existing approaches is the computational bottl…
PICO: Primitive Imitation for COntrol
Corban G. Rivera, Katie M. Popek, Chace Ashcraft +3
In this work, we explore a novel framework for control of complex systems called Primitive Imitation for Control PICO. The approach combines ideas from imitation learning, task dec…
Visual Robot Task Planning
Chris Paxton, Yotam Barnoy, Kapil Katyal +2
Prospection, the act of predicting the consequences of many possible futures, is intrinsic to human planning and action, and may even be at the root of consciousness. Surprisingly,…
Occupancy Map Prediction Using Generative and Fully Convolutional Networks for Vehicle Navigation
Kapil Katyal, Katie Popek, Chris Paxton +4
Fast, collision-free motion through unknown environments remains a challenging problem for robotic systems. In these situations, the robot's ability to reason about its future moti…
Learning to Imagine Manipulation Goals for Robot Task Planning
Chris Paxton, Kapil Katyal, Christian Rupprecht +2
Prospection is an important part of how humans come up with new task plans, but has not been explored in depth in robotics. Predicting multiple task-level is a challenging problem…