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Computer Science
Netherlands
2025

D-Index & Metrics

Computer Science

D-Index
51
Citations
10077
World Ranking
5353
National Ranking
82

Research.com Recognitions

  • 2025 - Research.com Computer Science in Netherlands Leader Award
  • 2022 - Research.com Computer Science in Netherlands Leader Award

Overview

Rudy R. Negenborn is affiliated with Delft University of Technology in the Netherlands. Their research spans a broad range of topics primarily situated within the field of Engineering.

Their main fields of study include:

  • Engineering

Subfields of study where they have contributed extensively are:

  • Industrial and Manufacturing Engineering
  • Ocean Engineering
  • Control and Systems Engineering
  • Automotive Engineering
  • Environmental Engineering

Negenborn's work focuses on topics such as:

  • Maritime Navigation and Safety
  • Maritime Ports and Logistics
  • Maritime Transport Emissions and Efficiency
  • Vehicle Routing Optimization Methods
  • Transportation and Mobility Innovations
  • Underwater Vehicles and Communication Systems
  • Robotic Path Planning Algorithms

The scientist has published in several venues with notable frequency, including:

  • IFAC-PapersOnLine
  • Ocean Engineering
  • IEEE Transactions on Intelligent Transportation Systems
  • Zenodo (CERN European Organization for Nuclear Research)
  • Transportation Research Part E Logistics and Transportation Review

Recent papers authored or co-authored by Negenborn include:

  • "Dynamic anti-collision A-star algorithm for multi-ship encounter situations," 2021, Applied Ocean Research
  • "A multi-objective maintenance strategy optimization framework for offshore wind farms considering uncertainty," 2022, Applied Energy
  • "Autonomous ships are on the horizon: here's what we need to know," 2023, Nature
  • "A ship collision avoidance system for human-machine cooperation during collision avoidance," 2020, Ocean Engineering
  • "A novel method for joint optimization of the sailing route and speed considering multiple environmental factors for more energy efficient shipping," 2020, Ocean Engineering

Negenborn collaborates frequently with several co-authors, notably:

  • Bilge Atasoy
  • Vasso Reppa
  • Frederik Schulte
  • Xiaoli Jiang
  • Zhe Du

Best Publications

  • Design and control of hybrid power and propulsion systems for smart ships: A review of developments

    R.D. Geertsma;R.R. Negenborn;K. Visser;J.J. Hopman

  • Distributed Model Predictive Control: An Overview and Roadmap of Future Research Opportunities

    R.R. Negenborn;J.M. Maestre

  • Ship collision avoidance methods : State-of-the-art

    Yamin Huang;Linying Chen;Pengfei Chen;Rudy R. Negenborn

  • Distributed Model Predictive Control Made Easy

    Jos M. Maestre;Rudy R. Negenborn

  • Multi-agent model predictive control for transportation networks: Serial versus parallel schemes

    R. R. Negenborn;B. De Schutter;J. Hellendoorn

  • Demand Response With Micro-CHP Systems

    Michiel Houwing;Rudy R Negenborn;Bart De Schutter

  • Distributed model predictive control of irrigation canals

    Rudy R. Negenborn;Peter-Jules van Overloop;Tamás Keviczky;Bart De Schutter

  • A comparative analysis of distributed MPC techniques applied to the HD-MPC four-tank benchmark

    I. Alvarado;D. Limon;D. Muñoz de la Peña;J.M. Maestre

  • Multi-agent model predictive control with applications to power networks

    R.R. Negenborn

  • Ship energy management for hybrid propulsion and power supply with shore charging

    M. Kalikatzarakis;R.D. Geertsma;E.J. Boonen;K. Visser

  • Robot Localization and Kalman Filters

    Rudy Negenborn

  • Kalman Filter-Based Distributed Predictive Control of Large-Scale Multi-Rate Systems: Application to Power Networks

    S. Roshany-Yamchi;M. Cychowski;R. R. Negenborn;B. De Schutter

  • Distributed model predictive control for vessel train formations of cooperative multi-vessel systems

    Linying Chen;Hans Hopman;Rudy R. Negenborn

  • Intermodal freight transport planning – A receding horizon control approach

    Le Li;Rudy R. Negenborn;Bart De Schutter

  • Trajectory tracking of autonomous vessels using model predictive control

    Huarong Zheng;Rudy R. Negenborn;Gabriel Lodewijks

  • Model-based predictive control applied to multi-carrier energy systems

    Michele Arnold;Rudy R. Negenborn;Goran Andersson;Bart De Schutter

  • Dynamic optimization of ship energy efficiency considering time-varying environmental factors

    Kai Wang;Kai Wang;Xinping Yan;Yupeng Yuan;Yupeng Yuan;Xiaoli Jiang

  • Energy-aware control for automated container terminals using integrated flow shop scheduling and optimal control

    Jianbin Xin;Rudy R. Negenborn;Gabriël Lodewijks

  • Energy-efficient shipping: An application of big data analysis for optimizing engine speed of inland ships considering multiple environmental factors

    Xinping Yan;Kai Wang;Kai Wang;Yupeng Yuan;Yupeng Yuan;Xiaoli Jiang

  • Distributed coordination for collision avoidance of multiple ships considering ship maneuverability

    Shijie Li;Jialun Liu;Rudy R. Negenborn

  • Synchromodal container transportation: An overview of current topics and research opportunities

    Bart van Riessen;Bart van Riessen;Rudy R. Negenborn;Rommert Dekker

  • Fast ADMM for Distributed Model Predictive Control of Cooperative Waterborne AGVs

    Huarong Zheng;Rudy R. Negenborn;Gabriel Lodewijks

  • Multi-agent model predictive control for transportation networks: serial versus parallel schemes

    Rudy R. Negenborn;Bart De Schutter;Hans Hellendoorn

Frequent Co-Authors

B. De Schutter
B. De Schutter Delft University of Technology
Bart De Schutter
Bart De Schutter Delft University of Technology
Rommert Dekker
Rommert Dekker Erasmus University Rotterdam
Xinping Yan
Xinping Yan Wuhan University of Technology
Hans Hellendoorn
Hans Hellendoorn Delft University of Technology
Hideaki Ishii
Hideaki Ishii Tokyo Institute of Technology
Nick van de Giesen
Nick van de Giesen Delft University of Technology

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