Persistent Coverage By A Drone Team Simulation

Persistent Coverage By A Drone Team Simulation Information Guide

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Details Persistent Coverage by 2 Drone teams Simulation Guide

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Recent Updates

Information Persistent Coverage Control by Drone Team Experiment Guide

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3D Object Monitoring by Persistent Coverage Control on a Sphere

Persistent Coverage Control with 3 drones

Equitable Persistent Coverage

Coverage Mission Simulation | Task 1 | 2 Drones | 100 Obstacles | No Attacks

Coverage Mission Simulation | Task 3 | 15 Drones | 100 Obstacles | No Attacks

Coverage Mission Simulation | Task 2 | 3 Drones | 100 Obstacles | No Attacks

Persistent Coverage Control with CBFs

Coverage-Recon Simulation (4 Drones, Map Feedback, 3D Grid, Jₜₕ = 50%)

Self-awarness in a drone swarm for the complete coverage of its surroundings

Enhancing Drone Operations with Simulation Webinar (AirborneSIM)

Spatial Scheduling of Informative Meetings for Multi-Agent Persistent Coverage

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Last Updated: September 30, 2026

Future Outlook

Details Persistent Coverage Control by Drone Team (with Energy Management) Guide

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Summary

We show the performance of a path planning algorithm for a Deep Reinforcement Learning for Multi-Agent Systems in Multicriteria Missions Author: Nicholas Scharan Cysne the source code at: github.com/miquel-espinosa/anti-flocking. Supplementary video for our RAL+ICRA 2020 video. Link to additional visualization: youtu.be/gLdqK2m3COo.

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