Media Summary: ... We present behavior-based cooperative navigation for mobile Title: Learning to Coordinate for a Worker-Station ANTS/SWARM 2026 paper We study the problem of deploying R mobile

Safe Multi Robot Exploration Using - Detailed Analysis & Overview

... We present behavior-based cooperative navigation for mobile Title: Learning to Coordinate for a Worker-Station ANTS/SWARM 2026 paper We study the problem of deploying R mobile This video accompanies the paper: Barisic et al: " Heriot-Watt University School of Mathematical and Computer Sciences Master in This video shows the achievement of the ICARE team that participated to the 2022 Edition of the CoHoMa Challenge, organizedĀ ...

Abstract: Robust motion planning is a well-studied problem in the Videos of Tests 1 and 2 reported in: Anna Mannucci, Lucia Pallottino and Federico Pecora. Provably

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Safe Multi-Robot Exploration using Symbolic Control
Review of multi-robot exploration || How can multiple robots map together an environment?
Safe Learning for Multi Robot Mapless Exploration - IEEE Transactions on Vehicular Technology
Safe Multi-Agent Reinforcement Learning for Behavior-Based Cooperative Navigation
Multi-Robot Gaussian Processes-Based Entropy-Driven Exploration
Learning to Coordinate for a Worker-Station Multi-robot System in Planar Coverage Tasks
Multi-Robot Visibility-Based Connected Exploration
Multi-robot System for Counter-UAS
Multi-Robot System - Frontier exploration: fast approach
Human-Robot Interaction in Multi-Robot Exploration: Team ICARE (Challenge CoHoMa 2022)
A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance
Provably Safe Multi-Robot Coordination with Unreliable Communication - Tests in Simulation
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Safe Multi-Robot Exploration using Symbolic Control

Safe Multi-Robot Exploration using Symbolic Control

Multi

Review of multi-robot exploration || How can multiple robots map together an environment?

Review of multi-robot exploration || How can multiple robots map together an environment?

New to

Safe Learning for Multi Robot Mapless Exploration - IEEE Transactions on Vehicular Technology

Safe Learning for Multi Robot Mapless Exploration - IEEE Transactions on Vehicular Technology

When

Safe Multi-Agent Reinforcement Learning for Behavior-Based Cooperative Navigation

Safe Multi-Agent Reinforcement Learning for Behavior-Based Cooperative Navigation

... We present behavior-based cooperative navigation for mobile

Multi-Robot Gaussian Processes-Based Entropy-Driven Exploration

Multi-Robot Gaussian Processes-Based Entropy-Driven Exploration

Mobile

Learning to Coordinate for a Worker-Station Multi-robot System in Planar Coverage Tasks

Learning to Coordinate for a Worker-Station Multi-robot System in Planar Coverage Tasks

Title: Learning to Coordinate for a Worker-Station

Multi-Robot Visibility-Based Connected Exploration

Multi-Robot Visibility-Based Connected Exploration

ANTS/SWARM 2026 paper https://ants2026.org/ We study the problem of deploying |R| mobile

Multi-robot System for Counter-UAS

Multi-robot System for Counter-UAS

This video accompanies the paper: Barisic et al: "

Multi-Robot System - Frontier exploration: fast approach

Multi-Robot System - Frontier exploration: fast approach

Heriot-Watt University School of Mathematical and Computer Sciences Master in

Human-Robot Interaction in Multi-Robot Exploration: Team ICARE (Challenge CoHoMa 2022)

Human-Robot Interaction in Multi-Robot Exploration: Team ICARE (Challenge CoHoMa 2022)

This video shows the achievement of the ICARE team that participated to the 2022 Edition of the CoHoMa Challenge, organizedĀ ...

A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance

A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance

Abstract: Robust motion planning is a well-studied problem in the

Provably Safe Multi-Robot Coordination with Unreliable Communication - Tests in Simulation

Provably Safe Multi-Robot Coordination with Unreliable Communication - Tests in Simulation

Videos of Tests 1 and 2 reported in: Anna Mannucci, Lucia Pallottino and Federico Pecora. Provably

SEER: Safe Efficient Exploration for Aerial Robots using Learning to Predict Information Gain

SEER: Safe Efficient Exploration for Aerial Robots using Learning to Predict Information Gain

We address the problem of efficient 3-D