497 citations · 2.1k across the 297 of their papers we have counts for
6 papers · 2 filters
Know Where You're Uncertain When Planning with Multimodal Foundation Models: A Formal Framework
Neel P. Bhatt, Yunhao Yang, Rohan Siva +3
Multimodal foundation models offer a promising framework for robotic perception and planning by processing sensory inputs to generate actionable plans. However, addressing uncertai…
MultiNash-PF: A Particle Filtering Approach for Computing Multiple Local Generalized Nash Equilibria in Trajectory Games
Maulik Bhatt, Iman Askari, Yue Yu +3
Modern robotic systems frequently engage in complex multi-agent interactions, many of which are inherently multi-modal, i.e., they can lead to multiple distinct outcomes. To intera…
Zero-Shot Transfer of Neural ODEs
Tyler Ingebrand, Adam J. Thorpe, Ufuk Topcu
Autonomous systems often encounter environments and scenarios beyond the scope of their training data, which underscores a critical challenge: the need to generalize and adapt to u…
Scalable Networked Feature Selection with Randomized Algorithm for Robot Navigation
Vivek Pandey, Arash Amini, Guangyi Liu +4
We address the problem of sparse selection of visual features for localizing a team of robots navigating an unknown environment, where robots can exchange relative position measure…
Online Foundation Model Selection in Robotics
Po-han Li, Oyku Selin Toprak, Aditya Narayanan +2
Foundation models have recently expanded into robotics after excelling in computer vision and natural language processing. The models are accessible in two ways: open-source or pai…
Auto-Encoding Bayesian Inverse Games
Xinjie Liu, Lasse Peters, Javier Alonso-Mora +2
When multiple agents interact in a common environment, each agent's actions impact others' future decisions, and noncooperative dynamic games naturally capture this coupling. In in…