7 citations · 7 across the 5 of their papers we have counts for
5 papers
Visual Navigation Transformer with Pose Attention
Beiming Li, Jaime Romero, Jonathan Diller +2
Learned navigation policies typically consume observations as a temporally ordered history, with positional encodings tying each observation to when it was seen, making it difficul…
MAST: Multi-Agent Spatial Transformer for Learning to Collaborate
Damian Owerko, Frederic Vatnsdal, Saurav Agarwal +2
This article presents a novel multi-agent spatial transformer (MAST) for learning communication policies in large-scale decentralized and collaborative multi-robot systems (DC-MRS)…
Scalable Multi Agent Diffusion Policies for Coverage Control
Frederic Vatnsdal, Romina Garcia Camargo, Saurav Agarwal +1
We propose MADP, a novel diffusion-model-based approach for collaboration in decentralized robot swarms. MADP leverages diffusion models to generate samples from complex and high-d…
Constrained Learning for Decentralized Multi-Objective Coverage Control
Juan Cervino, Saurav Agarwal, Vijay Kumar +1
The multi-objective coverage control problem requires a robot swarm to collaboratively provide sensor coverage to multiple heterogeneous importance density fields IDFs simultaneous…
LPAC: Learnable Perception-Action-Communication Loops with Applications to Coverage Control
Saurav Agarwal, Ramya Muthukrishnan, Walker Gosrich +2
Coverage control is the problem of navigating a robot swarm to collaboratively monitor features or a phenomenon of interest not known a priori. The problem is challenging in decent…