activity
20162026
most citedGenerative Adversarial Imitation from Observation

90 citations · 230 across the 45 of their papers we have counts for

collaborators

52 papers

cs.RO2026

Adapting Generalist Vehicle Models for High-Speed MPC Across Terrains

Rwik Rana, Jesse Quattrociocchi, Christian Ellis +3

High-speed off-road autonomy requires precise closed-loop control for a target vehicle while remaining robust across changing terrains. Recent forward kinodynamic (FKD) prediction…

cs.RO2026

OVerSeeC: Open-Vocabulary Costmap Generation from Satellite Images and Natural Language

Rwik Rana, Jesse Quattrociocchi, Dongmyeong Lee +5

Aerial imagery provides essential global context for autonomous navigation, enabling route planning at scales inaccessible to onboard sensing. We address the problem of generating…

cs.RO2025★ 1 cited

BEV-Patch-PF: Particle Filtering with BEV-Aerial Feature Matching for Off-Road Geo-Localization

Dongmyeong Lee, Jesse Quattrociocchi, Christian Ellis +5

We propose BEV-Patch-PF, a GPS-free sequential geo-localization system that integrates a particle filter with learned bird's-eye-view (BEV) and aerial feature maps. From onboard RG…

cs.RO2025

Terrain Costmap Generation via Scaled Preference Conditioning

Luisa Mao, Garrett Warnell, Peter Stone +1

Successful autonomous robot navigation in off-road domains requires the ability to generate high-quality terrain costmaps that are able to both generalize well over a wide variety…

cs.RO2025

ComposableNav: Instruction-Following Navigation in Dynamic Environments via Composable Diffusion

Zichao Hu, Chen Tang, Michael J. Munje +6

This paper considers the problem of enabling robots to navigate dynamic environments while following instructions. The challenge lies in the combinatorial nature of instruction spe…

cs.RO2025

SocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation

Michael J. Munje, Chen Tang, Shuijing Liu +6

Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-Language Models (VLMs) exhibit…