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
Massive introduction of
Sensing, Computation, and Communication Technologies
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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]
Efficient multi-scenario model predictive control for water resources management with ensemble streamflow forecasts
"Model Predictive Control (MPC) is one of the most advanced real-time control techniques that has been widely applied to water resources management (WRM). MPC can manage the water system in a holistic manner and has a flexible structure to incorporate specific elements, such as setpoints and constraints. Therefore, MPC has shown its versatile performance in many branches of WRM. Nonetheless, with t..." [ More...] X. Tian, R.R. Negenborn, P.J. van Overloop, J.M. Maestre, A. Sadowska, N. van de Giesen. Efficient multi-scenario model predictive control for water resources management with ensemble streamflow forecasts. Advances in Water Resources, vol. 109, pp. 58-68, 2017.
[ Publications: Recent]
[ In pictures]
[ Control & Coordination]
[ Transport Logistics]
Recently added publications
L. Wang, Q. Wu, J. Liu, S. Li, R.R. Negenborn. State-of-the-art research on motion control of maritime autonomous surface ships. Accepted for publication in Journal of Marine Science and Engineering, 2019. S. Xie, V. Garofano, X. Chu, R.R. Negenborn. Model predictive ship collision avoidance based on Q-learning beetle swarm antenna search and neural networks. Ocean Engineering, vol. 193, no. 106609, December 2019. S. Li, J. Liu, R.R. Negenborn, F. Ma. Optimizing the joint collision avoidance operations of multiple ships from an overall perspective. Ocean Engineering, vol. 191 (2019), no. 106511, 2019. L. Chen, J.J. Hopman, R.R. Negenborn. Distributed model predictive control for cooperative floating object transport
with multi-vessel systems. Ocean Engineering, vol. 191 (2019), no. 106515, 2019. Y. Huang, L. Chen, P. Chen, R.R. Negenborn, P.H.A.J.M. van Gelder. Ship collision avoidance methods: State-of-the-art. Safety Science, vol. 121 (2020), pp. 451-473, 2019.
How will autonomous ships work?
Research in Sketches
Active topic cloud (past 3 years)
transport over water,
control of ships
transportation networks, inter-terminal transport
reinforcement learning, Kalman filters, learning robots
The Brain of TU Delft
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"
"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
Inter Terminal Transport at the Port of Rotterdam
Towards guaranteed port accessibility
Innovational Research Incentives
Scheme 2010 VENI
AIDA -- The Booklet
Automatic Research Positioning & Trend Identification
Journal Special Issues
Computational Transport Logistics at Work
(Special issue of Transportation Research Part E)
(Special issue of SWZ Maritime 2017/02)
(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?