research
∙
03/29/2023
Legged Robots for Object Manipulation: A Review
Legged robots can have a unique role in manipulating objects in dynamic,...
share
research
∙
03/11/2023
Spatio-Temporal Attention Network for Persistent Monitoring of Multiple Mobile Targets
This work focuses on the persistent monitoring problem, where a set of t...
research
∙
03/09/2023
Intent-based Deep Reinforcement Learning for Multi-agent Informative Path Planning
In multi-agent informative path planning (MAIPP), agents must collective...
research
∙
03/01/2023
SCRIMP: Scalable Communication for Reinforcement- and Imitation-Learning-Based Multi-Agent Pathfinding
Trading off performance guarantees in favor of scalability, the Multi-Ag...
research
∙
01/27/2023
ARiADNE: A Reinforcement learning approach using Attention-based Deep Networks for Exploration
In autonomous robot exploration tasks, a mobile robot needs to actively ...
research
∙
04/07/2022
Distributed Reinforcement Learning for Robot Teams: A Review
Purpose of review: Recent advances in sensing, actuation, and computatio...
research
∙
01/28/2022
FCMNet: Full Communication Memory Net for Team-Level Cooperation in Multi-Agent Systems
Decentralized cooperation in partially-observable multi-agent systems re...
research
∙
12/01/2021
A general locomotion control framework for serially connected multi-legged robots
Serially connected robots are promising candidates for performing tasks ...
research
∙
09/09/2021
DAN: Decentralized Attention-based Neural Network to Solve the MinMax Multiple Traveling Salesman Problem
The multiple traveling salesman problem (mTSP) is a well-known NP-hard p...
research
∙
03/30/2021
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World
The Flatland competition aimed at finding novel approaches to solve the ...
research
∙
12/10/2020
Flatland-RL : Multi-Agent Reinforcement Learning on Trains
Efficient automated scheduling of trains remains a major challenge for m...
research
∙
10/16/2020
PRIMAL2: Pathfinding via Reinforcement and Imitation Multi-Agent Learning – Lifelong
Multi-agent path finding (MAPF) is an indispensable component of large-s...
research
∙
06/15/2020
ForMIC: Foraging via Multiagent RL with Implicit Communication
Multi-agent foraging (MAF) involves distributing a team of agents to sea...
research
∙
01/24/2019
Distributed Learning of Decentralized Control Policies for Articulated Mobile Robots
State-of-the-art distributed algorithms for reinforcement learning rely ...
research
∙
09/10/2018
PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning
Multi-agent path finding (MAPF) is an essential component of many large-...
research
∙
03/05/2018