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Javier Yu

7 accepted papers

2026

VISTA: Open-Vocabulary, Task-Relevant Robot Exploration With Online Semantic Gaussian Splatting

RA-L 2026

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 quality in areas most relevant for task completion. Given an open-vocabulary search instruction (e.g., “find a person”), VISTA

Cited by 4SourcecodeScholar
2026

VISTA: Open-Vocabulary, Task-Relevant Robot Exploration with Online Semantic Gaussian Splatting

ICRA 2026poster

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 quality in areas most relevant for task completion. Given an open-vocabulary search instruction (e.g., "find a person"), VISTA…

2025

A Control Barrier Function for Safe Navigation with Online Gaussian Splatting Maps

ICRA 2025

SAFER-Splat (Simultaneous Action Filtering and Environment Reconstruction) is a real-time, scalable, and minimally invasive safety filter, based on control barrier functions, for safe robotic navigation in a detailed map constructed at runtime using Gaussian Splatting (GSplat). We propose a novel Co

Cited by 17SourcecodeScholar
2025

SOUS VIDE: Cooking Visual Drone Navigation Policies in a Gaussian Splatting Vacuum

RA-L 2025

We propose a new simulator, training approach, and policy architecture, collectively called SOUS VIDE, for end-to-end visual drone navigation. Our trained policies exhibit zero-shot sim-to-real transfer with robust real-world performance using only onboard perception and computation. Our simulator,

Cited by 18SourceScholar
2022

DiNNO: Distributed Neural Network Optimization for Multi-Robot Collaborative Learning

RA-L 2022

We present DiNNO, a distributed algorithm that enables a group of robots to collaboratively optimize a deep neural network model while communicating over a mesh network. Each robot only has access to its own data and maintains its own version of the neural network, but eventually learns a model that

Cited by 51SourceScholar
2020

Distributed Multi-Target Tracking for Autonomous Vehicle Fleets

ICRA 2020poster

We present a scalable distributed target tracking algorithm based on the alternating direction method of multipliers that is well-suited for a fleet of autonomous cars communicating over a vehicle-to-vehicle network. Each sensing vehicle communicates with its neighbors to execute iterations of a Kal…

Cited by 41SourceScholar