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Manuel Boldrer

5 accepted papers

2026

Distributed Lloyd-Based Algorithm for Uncertainty-Aware Multi-Robot Under-Canopy Flocking

RA-L 2026

In this letter, we present a distributed algorithm for flocking in complex environments that operates at constant altitude, without explicit communication, no a priori information about the environment, and by using only on-board sensing and computation capabilities. We provide sufficient conditions

Cited by 1SourceScholar
2023

Time-Inverted Kuramoto Model Meets Lissajous Curves: Multi-Robot Persistent Monitoring and Target Detection

RA-L 2023

This letter proposes a distributed strategy to achieve both persistent monitoring and target detection in a rectangular and obstacle-free environment. Each robot has to repeatedly follow a smooth trajectory and avoid collisions with other robots. To achieve this goal, we rely on the time-inverted Ku

Cited by 8SourceScholar
2021

Graph Connectivity Control of a Mobile Robot Network With Mixed Dynamic Multi-Tasks

RA-L 2021

Given a team composed of groups of robots with different abilities and different tasks, we propose a control solution that allows maintaining the connectivity between the agents whilst securing the execution of the different tasks assigned to the team. The specific notion of connectivity adopted her

Cited by 9SourceScholar
2020

Lloyd-based Approach for Robots Navigation in Human-shared environments

IROS 2020poster

We present a Lloyd-based navigation solution for robots that are required to move in a dynamic environment, where static obstacles (e.g, furnitures, parked cars) and unpredicted moving obstacles (e.g., humans, other robots) have to be detected and avoided on the fly. The algorithm can be computed in…

Cited by 7SourceScholar
2020

Socially-Aware Reactive Obstacle Avoidance Strategy Based on Limit Cycle

RA-L 2020

The letter proposes a combination of ideas to support navigation for a mobile robot across dynamic environments, cluttered with obstacles and populated by human beings. The combination of the classical potential field methods and limit cycle based approach with an innovative shape for the limit cycl

Cited by 22SourceScholar