13 citations · 28 across the 25 of their papers we have counts for
14 papers · 1 filter
FAST-Splat: Fast, Ambiguity-Free Semantics Transfer in Gaussian Splatting
Ola Shorinwa, Jiankai Sun, Mac Schwager
We present FAST-Splat for fast, ambiguity-free semantic Gaussian Splatting, which seeks to address the main limitations of existing semantic Gaussian Splatting methods, namely: slo…
DisCo: Distributed Contact-Rich Trajectory Optimization for Forceful Multi-Robot Collaboration
Ola Shorinwa, Matthew Devlin, Elliot W. Hawkes +1
We present DisCo, a distributed algorithm for contact-rich, multi-robot tasks. DisCo is a distributed contact-implicit trajectory optimization algorithm, which allows a group of ro…
ARCH: Hierarchical Hybrid Learning for Long-Horizon Contact-Rich Robotic Assembly
Jiankai Sun, Aidan Curtis, Yang You +8
Generalizable long-horizon robotic assembly requires reasoning at multiple levels of abstraction. While end-to-end imitation learning (IL) is a promising approach, it typically req…
E2Map: Experience-and-Emotion Map for Self-Reflective Robot Navigation with Language Models
Chan Kim, Keonwoo Kim, Mintaek Oh +10
Large language models (LLMs) have shown significant potential in guiding embodied agents to execute language instructions across a range of tasks, including robotic manipulation an…
SAFER-Splat: A Control Barrier Function for Safe Navigation with Online Gaussian Splatting Maps
Timothy Chen, Aiden Swann, Javier Yu +4
SAFER-Splat (Simultaneous Action Filtering and Environment Reconstruction) is a real-time, scalable, and minimally invasive action filter, based on control barrier functions, for s…
Gen-Swarms: Adapting Deep Generative Models to Swarms of Drones
Carlos Plou, Pablo Pueyo, Ruben Martinez-Cantin +3
Gen-Swarms is an innovative method that leverages and combines the capabilities of deep generative models with reactive navigation algorithms to automate the creation of drone show…
Safe, Out-of-Distribution-Adaptive MPC with Conformalized Neural Network Ensembles
Jose Leopoldo Contreras, Ola Shorinwa, Mac Schwager
We present SODA-MPC, a Safe, Out-of-Distribution-Adaptive Model Predictive Control algorithm, which uses an ensemble of learned models for prediction, with a runtime monitor to fla…
How Generalizable Is My Behavior Cloning Policy? A Statistical Approach to Trustworthy Performance Evaluation
Joseph A. Vincent, Haruki Nishimura, Masha Itkina +3
With the rise of stochastic generative models in robot policy learning, end-to-end visuomotor policies are increasingly successful at solving complex tasks by learning from human d…
Splat-MOVER: Multi-Stage, Open-Vocabulary Robotic Manipulation via Editable Gaussian Splatting
Ola Shorinwa, Johnathan Tucker, Aliyah Smith +5
We present Splat-MOVER, a modular robotics stack for open-vocabulary robotic manipulation, which leverages the editability of Gaussian Splatting (GSplat) scene representations to e…
CLIPSwarm: Generating Drone Shows from Text Prompts with Vision-Language Models
Pablo Pueyo, Eduardo Montijano, Ana C. Murillo +1
This paper introduces CLIPSwarm, a new algorithm designed to automate the modeling of swarm drone formations based on natural language. The algorithm begins by enriching a provided…
Touch-GS: Visual-Tactile Supervised 3D Gaussian Splatting
Aiden Swann, Matthew Strong, Won Kyung Do +3
In this work, we propose a novel method to supervise 3D Gaussian Splatting (3DGS) scenes using optical tactile sensors. Optical tactile sensors have become widespread in their use…
Splat-Nav: Safe Real-Time Robot Navigation in Gaussian Splatting Maps
Timothy Chen, Ola Shorinwa, Joseph Bruno +6
We present Splat-Nav, a real-time robot navigation pipeline for Gaussian Splatting (GSplat) scenes, a powerful new 3D scene representation. Splat-Nav consists of two components: 1)…
Distributed Quasi-Newton Method for Multi-Agent Optimization
Ola Shorinwa, Mac Schwager
We present a distributed quasi-Newton (DQN) method, which enables a group of agents to compute an optimal solution of a separable multi-agent optimization problem locally using an…
CineMPC: A Fully Autonomous Drone Cinematography System Incorporating Zoom, Focus, Pose, and Scene Composition
Pablo Pueyo, Juan Dendarieta, Eduardo Montijano +2
We present CineMPC, a complete cinematographic system that autonomously controls a drone to film multiple targets recording user-specified aesthetic objectives. Existing solutions…