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02/11/2021
Large Scale Distributed Collaborative Unlabeled Motion Planning with Graph Policy Gradients
In this paper, we present a learning method to solve the unlabelled moti...
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06/11/2020
Graph Neural Networks for Motion Planning
This paper investigates the feasibility of using Graph Neural Networks (...
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09/24/2019
Graph Policy Gradients for Large Scale Unlabeled Motion Planning with Constraints
In this paper, we present a learning method to solve the unlabelled moti...
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07/11/2019
Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints
In this paper, we present a learning approach to goal assignment and tra...
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07/08/2019
Graph Policy Gradients for Large Scale Robot Control
In this paper, we consider the problem of learning policies to control a...
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02/19/2019
Learning Task Agnostic Sufficiently Accurate Models
For complex real-world systems, designing controllers are a difficult ta...
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05/22/2018
Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients
In this paper, we explore using deep reinforcement learning for problems...
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03/05/2018
Learning Sample-Efficient Target Reaching for Mobile Robots
In this paper, we propose a novel architecture and a self-supervised pol...
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09/17/2017