collaborators

9 papers

cs.RO2026

Strategizing at Speed: A Learned Model Predictive Game for Multi-Agent Drone Racing

Andrei-Carlo Papuc, Lasse Peters, Sihao Sun +2

Autonomous drone racing pushes the boundaries of high-speed motion planning and multi-agent strategic decision-making. Success in this domain requires drones not only to navigate a…

cs.RO2026

STEM: Semantic Target Search and Exploration using MAVs in Cluttered Environments

Nikhil Sethi, Max Lodel, Laura Ferranti +2

Autonomous target search is crucial for deploying Micro Aerial Vehicles (MAVs) in emergency response and rescue missions. Existing approaches either focus on 2D semantic navigation…

eess.SY2026

Homotopy-Guided Potential Games for Congestion-Aware Navigation

Mohammed Irshadh Ismaaeel Sathyamangalam Imran, Lasse Peters, Michael Khayyat +3

We address the multi-agent motion planning problem where interactions, collisions, and congestion co-exist. Conventional game-theoretic planners capture interactions among agents b…

cs.RO2025

From Data to Safe Mobile Robot Navigation: An Efficient and Modular Robust MPC Design Pipeline

Dennis Benders, Johannes Köhler, Robert Babuška +2

Model predictive control (MPC) is a powerful strategy for planning and control in autonomous mobile robot navigation. However, ensuring safety in real-world deployments remains cha…

cs.RO2025

A Step-by-step Guide on Nonlinear Model Predictive Control for Safe Mobile Robot Navigation

Dennis Benders, Laura Ferranti, Johannes Köhler

Designing a model predictive control (MPC) scheme that enables a mobile robot to safely navigate through an obstacle-filled environment is a complicated yet essential task in robot…

eess.SY2025

Distributed Attack-Resilient Platooning Against False Data Injection

Lorenzo Lyons, Manuel Boldrer, Laura Ferranti

This paper presents a novel distributed vehicle platooning control and coordination strategy. We propose a distributed predecessor-follower CACC scheme that allows to choose an arb…