6 citations · 7 across the 4 of their papers we have counts for
6 papers
Fast and scalable multi-robot deployment planning under connectivity constraints
Yaroslav Marchukov, Luis Montano
In this paper we develop a method to coordinate the deployment of a multi-robot team to reach some locations of interest, so-called primary goals, and to transmit the information f…
Multi-agent coordination for data gathering with periodic requests and deliveries
Yaroslav Marchukov, Luis Montano
In this demo work we develop a method to plan and coordinate a multi-agent team to gather information on demand. The data is periodically requested by a static Operation Center (OC…
Communication-aware planning for robot teams deployment
Yaroslav Marchukov, Luis Montano
In the present work we address the problem of deploying a team of robots in a scenario where some locations of interest must be reached. Thus, a planning for a deployment is requir…
Multi-robot coordination for connectivity recovery after unpredictable environment changes
Yaroslav Marchukov, Luis Montano
In the present paper we develop a distributed method to reconnect a multi-robot team after connectivity failures, caused by unpredictable environment changes, i.e. appearance of ne…
Multi-agent coordination for on-demand data gathering with periodic information upload
Yaroslav Marchukov, Luis Montano
In this paper we develop a method for planning and coordinating a multi-agent team deployment to periodically gather information on demand. A static operation center (OC) periodica…
Deep reinforcement learning oriented for real world dynamic scenarios
Diego Martinez, Luis Riazuelo, Luis Montano
Autonomous navigation in dynamic environments is a complex but essential task for autonomous robots. Recent deep reinforcement learning approaches show promising results to solve t…