Rudy Negenborn Full Professor, Head of Section Latest news: PhD position "Dynamic and Stochastic Fleet Management Models for Transportation and Logistics" @TUDelft now open fo… https://t.co/vXw5eCQtcw "Will the Corona virus put an end to globalisation?" -- colleague Wouter Beelaerts van Blokland provides food for t… https://t.co/cEsbZsctDr[More on Twitter] Main Publications Team & Themes Education Resume Personal

Transport Engineering and Logistics Dept. of Maritime and Transport Technology Delft University of Technology Mekelweg 2, 2628 CD  Delft The Netherlands Room B-3-300 How to reach Faculty 3mE How to reach my office tel: +31 (0) 15 27 86718 fax: +31 (0) 15 27 81397 contact form: Click here e-mail: r.r.negenborn@tudelft.nl secretary: Patty Bokop-van der Stap tel: +31 (0)15 27 86529 LinkedIn Twitter Autonomous Vessel Family Interacting Vessels Delfia-1 Star Delfia-1 [in action] Delfia-Amphibian SeaBax-Inside SeaBax-Outside Tito Neri Quality Care Hybrid Tug Friend of the Family: WUT-1 (Wuhan University of Technology) Friend of the Family: Vosper Perkasa (Wuhan University of Technology) Computational Logistics 2015 ICCL'15 - International Conference on Computational Logistics (ICCL) 2015 Delft, The Netherlands Main research interests: Coordination within and among transport hubs 4S Framework: Real-time coordination of Smart Equipment in Smart Hubs for Smart Ports in Smart Networks Anticipating the Massive introduction of Sensing, Computation, and Communication Technologies       Vacancies:    Flyer: [7 PhD and PostDoc positions opening soon]    More information on currently open vacancies? [Click here] Inauguration Speech on communication, logistics, autonomous ships, and multi-machine engineering "What if ships could talk?", or: Coordination for Real-Time Logistics [Watch the public presentation online] Spotlight publication Fast ADMM for distributed model predictive control of cooperative Waterborne AGVs "This article proposes a distributed predictive path following controller with arrival time awareness for multiple waterborne AGVs applied to Inter Terminal Transport (ITT). The goal is to design an efficient cooperative distributed algorithm that solves local problems in parallel and minimizes an overall objective. We model the ITT problem using waterborne AGVs with independent dynamics and object..." [More...] H. Zheng, R.R. Negenborn, G. Lodewijks. Fast ADMM for distributed model predictive control of cooperative Waterborne AGVs. IEEE Transactions on Control Systems Technology, vol. 25, no. 4, pp. 1406-1413, July 2017.    Publications: [Recent] [All] [In pictures] [Control & Coordination] [Transport Logistics] Recently added publications S. Li, J. Liu, R.R. Negenborn. Automatic docking for underactuated ships based on multi-objective nonlinear model predictive control. Accepted for publication in IEEE Access, 2020.    W. Guo, B. Atasoy, W.W.A. Beelaerts-van Blokland, R.R. Negenborn. A dynamic shipment matching problem in hinterland synchromodal transportation. Accepted for publication in Decision Support Systems, 2020.    J. Los, F. Schulte, M.T.J. Spaan, R.R. Negenborn. Collaborative vehicle routing when agents have mixed information sharing attitudes. In Transportation Research Procedia, pp. 94-101, 2020. Vol. 44. Open access.    S. Li, J. Liu, F. Ma, R.R. Negenborn. Autonomous ship docking based on nonlinear model predictive control. Accepted for the 21st IFAC World Congress (IFAC2020), Berlin, Germany, July 2020.    T. Hipolito, J.L. Nabais, M.A. Botto, R.R. Negenborn. Effective continuous-flow supply chains using centralized model predictive control. Accepted for the 21st IFAC World Congress (IFAC2020), Berlin, Germany, July 2020.    [More...] Infographics How will autonomous ships work? Books        Research in Sketches [More...] Active topic cloud (past 3 years) Keywords logistics, intermodal transport, container transport transport over water, control of ships transportation networks, inter-terminal transport water networks power networks, gas networks multi-agent systems, model predictive control, hybrid systems reinforcement learning, Kalman filters, learning robots The Brain of TU Delft H2020 MG-2-6-2019 -- NOVIMOVE: "Novel inland waterway transport concepts" Promoting Green Transport and Mobility: "AVATAR" NWO Topsector Water & Maritiem: Blauwe Route -- "TRiLOGy" and "READiNESS" Interreg 2 Seas: "ISHY: Implementation of Ship Hybridisation" A multi-machine engineering perspective H2020 EU.3.2.5 2017: Cross-cutting marine and maritime research: "Space@Sea -- Transport & Logistics" "Impulse Autonomous Shipping for Amsterdam 2018" SmartPort 2017 "Port Impact of Autonomous Ship Applications" NWO Social & Physical Sciences 2016 "Complexity Methods for Predictive Synchromodality" (COMET-PS) STW Perspectief 2015 Program "i-CAVE" Strategic Innovation Project AIDA: Automatic Identification of Research Trends STW Water 2015 Program "GasDrive" Topsector Water/STW Maritime 2013 Program "ShipDrive" Inter Terminal Transport at the Port of Rotterdam [More...]      Towards guaranteed port accessibility [More...] Innovational Research Incentives Scheme 2010 VENI Grant [More...] AIDA -- The Booklet Automatic Research Positioning & Trend Identification Journal Special Issues Computational Transport Logistics at Work (Special issue of Transportation Research Part E) Autonomous Ships (Special issue of SWZ Maritime 2017/02) Propulsion Systems (Special issue of SWZ Maritime 2015/10) Water Prediction and Control Technology (Special issue of Journal of Hydroinformatics) Videos on Inter Terminal Transport Opportunities for Real-Time Coordination Automated MTS and waterborne AGVs as solution?

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