7 citations · 8 across the 16 of their papers we have counts for
9 papers · 1 filter
Semantic-Metric Bayesian Risk Fields: Learning Robot Safety from Human Videos with a VLM Prior
Timothy Chen, Marcus Dominguez-Kuhne, Aiden Swann +2
Humans interpret safety not as a binary signal but as a continuous, context- and spatially-dependent notion of risk. While risk is subjective, humans form rational mental models th…
Conformal Safety Monitoring for Flight Testing: A Case Study in Data-Driven Safety Learning
Aaron O. Feldman, D. Isaiah Harp, Joseph Duncan +1
We develop a data-driven approach for runtime safety monitoring in flight testing, where pilots perform maneuvers on aircraft with uncertain parameters. Because safety violations c…
SketchPlan: Diffusion Based Drone Planning From Human Sketches
Sixten Norelius, Aaron O. Feldman, Mac Schwager
We propose SketchPlan, a diffusion-based planner that interprets 2D hand-drawn sketches over depth images to generate 3D flight paths for drone navigation. SketchPlan comprises two…
SINGER: An Onboard Generalist Vision-Language Navigation Policy for Drones
Maximilian Adang, JunEn Low, Ola Shorinwa +1
Large vision-language models have driven remarkable progress in open-vocabulary robot policies, e.g., generalist robot manipulation policies, that enable robots to complete complex…
VISTA: Open-Vocabulary, Task-Relevant Robot Exploration with Online Semantic Gaussian Splatting
Keiko Nagami, Timothy Chen, Javier Yu +5
We present VISTA (Viewpoint-based Image selection with Semantic Task Awareness), an active exploration method for robots to plan informative trajectories that improve 3D map qualit…
GRaD-Nav++: Vision-Language Model Enabled Visual Drone Navigation with Gaussian Radiance Fields and Differentiable Dynamics
Qianzhong Chen, Naixiang Gao, Suning Huang +4
Autonomous drones capable of interpreting and executing high-level language instructions in unstructured environments remain a long-standing goal. Yet existing approaches are const…
GRaD-Nav: Efficiently Learning Visual Drone Navigation with Gaussian Radiance Fields and Differentiable Dynamics
Qianzhong Chen, Jiankai Sun, Naixiang Gao +3
Autonomous visual navigation is an essential element in robot autonomy. Reinforcement learning (RL) offers a promising policy training paradigm. However existing RL methods suffer…
HAMMER: Heterogeneous, Multi-Robot Semantic Gaussian Splatting
Javier Yu, Timothy Chen, Mac Schwager
3D Gaussian Splatting offers expressive scene reconstruction, modeling a broad range of visual, geometric, and semantic information. However, efficient real-time map reconstruction…
Learning Robot Safety from Sparse Human Feedback using Conformal Prediction
Aaron O. Feldman, Joseph A. Vincent, Maximilian Adang +2
Ensuring robot safety can be challenging; user-defined constraints can miss edge cases, policies can become unsafe even when trained from safe data, and safety can be subjective. T…