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ELLIS Delft Talk by Javier Alonso-Mora

ELLIS Delft Talk by Javier Alonso-Mora 12 April 2022 16:00 (NOTE: the meeting moved from 5th -> 12th) This will be a hybrid meeting This meeting is open for all interested researchers. Motion Planning among Decision-Making Agents: Trajectory Optimization with Learned Cost Functions Abstract We move towards an era of smart cities, where autonomous vehicles will provide on-demand transportation while making our streets safer and mobile robots will coexist with humans. The motion plan of mobile robots and autonomous vehicles must, therefore, account for the interaction with other agents and consider that they are, as well, decision-making entities. For example, when humans drive a car, they are fully aware of their environment and how other drivers and pedestrians may react to their future actions. Towards this objective I will discuss several methods for motion planning and multi-robot coordination that leverage constrained optimization and reinforcement learning to achieve interactive behaviors with safety guarantees. Namely: using inverse reinforcement learning and social value estimation to achieve social behaviors; employing a learned policy to guide the motion planner in dense traffic scenarios or for information gathering; achieving social trajectories by learning a cost function from a dataset of human-driven vehicles; and learning to communicate the relevant information for multi-robot coordination. The methods are of broad applicability, including autonomous vehicles and aerial vehicles. Bio Javier Alonso-Mora is an Associate Professor at the Department of Cognitive Robotics of the Delft University of Technology, the director of the Autonomous Multi-robots Laboratory, a Principal Investigator at the Amsterdam Institute for Advanced Metropolitan Solutions and co-founder of The Routing Company. Previously, he was a Postdoctoral Associate at the Computer Science and Artificial Intelligence Lab (CSAIL) of the Massachusetts Institute of Technology. He received his Ph.D. degree in robotics from ETH Zurich, in partnership with Disney Research Zurich. He serves as associate editor for Springer Autonomous Robots, and has served as associate editor for the IEEE Robotics and Automation Letters, the Publications Chair for the IEEE International Symposium on Multi-Robot and Multi-Agent Systems 2021 and associate editor for ICRA, IROS and ICUAS. He is the recipient of several prizes and grants, including an ERC Starting Grant (2021), the ICRA Best Paper Award on Multi-robot Systems (2019), an Amazon Research Award (2019) and a talent scheme VENI award from the Netherlands Organisation for Scientific Research (2017). More info: https://www.autonomousrobots.nl/ To join this event, please contact Frans Oliehoek .

van Duijvenbode, J.R.

Profile TU Delft (2018 – current) Ph.D. candidate in Resource Engineering I obtained a MSc degree in the European Mining Course (EMC) from Delft University of Technology, Aalto University and RWTH Aachen. My master thesis was about: Development and Validation of Short-term Mine Planning Optimization Algorithms for a Sublevel Stoping Operation with Backfilling. Research PhD research into the behavioural Geology – Understanding how differences in geology influence metallurgical performance. The research topic consists of integrating collected information on metallurgical properties, directly or through proxies back into the resource model. The consideration of metallurgical costs is the only way forward to obtain truly optimized mining decisions, accounting for constraints and bottlenecks in the comminution circuit and chemical processing plant. This is important to better characterize metallurgical behavior of the plant feed, which allows for a morel optimal selection of process control settings. The envisioned solution will result in an increased recovery in combination with a lower utilization of energy and chemicals per tonne of processed material (lower environmental footprint). Consequently, overall OPEX will drop making lower grade ore economic while increasing the mineral resources that are available for conversion to ore reserves (lesser need to open up new mines). Moreover, a better characterization of mining blocks reduces the unintended processing of waste due to lower overall classification errors. Copromotor: Dr. M. Soleymani Shishvan Promotor(s): Dr. M. Buxton and Prof. Jan Dirk Jansen Jeroen van Duijvenbode PhD Candidate + 31 15 27 82262 J.R.vanDuijvenbode@tudelft.nl Faculty of Civil Engineering and Geosciences Building 23 Stevinweg 1 / PO-box 5048 2628 CN Delft / 2600 GA Delft Room number: 3.21

ELLIS Delft Talk by Guillaume Rongier

ELLIS Delft Talk by Guillaume Rongier Going beyond empirical relationships in geology: The example of total organic carbon 01 February 2022 16:00 Abstract While machine learning has a long history in geology, empirical relationships remain widely used. Through the example of total organic carbon (TOC), this talk will illustrate the close links between empirical relationships and machine learning, and the benefits of turning to machine learning. TOC is a measure of the proportion of organic carbon in rock samples typically gathered from boreholes. It can be used to assess the potential for hydrocarbons, understand rock mechanics, or assess reducing conditions for basin-hosted mineral systems, and is paramount when seeking to understand variations in paleo-environmental conditions. Since gathering and analyzing rock samples is expensive, empirical relationships have been developed to predict TOC from well logs, which are based on more widely available geophysical measurements into boreholes. Those empirical relationships come from geological and petrophysical principles implemented in mathematical models manually fitted to the data. This leads to several limitations, mainly poor generalization, inability to quantify uncertainties, time-consuming and subjective calibration that leads to reproducibility issues. But those empirical relationships can be rewritten as linear regressions, a simple change that solves many of the previous limitations. Turning to more advanced machine learning methods improves predictions by taking into account the non-linearity and variability in the data. Using the expert knowledge behind empirical relationships as input besides well logs improves the predictions as well: this shows that leveraging geological and petrophysical concepts through feature selection and engineering boosts machine learning performances. To join this event, please contact Frans Oliehoek .

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Researchers hand over Position Paper to Tweede Kamer

On behalf of the TU Delft PowerWeb Institute, researchers Kenneth Brunninx and Simon Tindemans are handing over a Position Paper to the Dutch Parliament on 14 November 2024, with a possible solution to the major grid capacity problems that are increasingly cropping up in the Netherlands. The Netherlands is unlikely to meet the 2030 climate targets, and one of the reasons for this is that large industry cannot switch to electricity fast enough, partly because of increasingly frequent problems around grid capacity and grid congestion. In all likelihood, those problems will actually increase this decade before they can decrease, the researchers argue. The solution offered by the TU Delft PowerWeb Institute researchers is the ‘flexible backstop’. With a flexible backstop, the current capacity of the power grid can be used more efficiently without sacrificing safety or reliability. A flexible backstop is a safety mechanism that automatically and quickly reduces the amount of electricity that an electric unit can draw from the grid (an electric charging station or a heat pump) or deliver (a PV installation). It is a small device connected or built into an electrical unit, such as a charging station or heat pump, that ‘communicates’ with the distribution network operator. In case of extreme stress on the network, the network operator sends a signal to the device to limit the amount of power. Germany recently introduced a similar system with electric charging stations. The backstop would be activated only in periods of acute congestion problems and could help prevent the last resort measure, which is cutting off electricity to users. ‘Upgrading the electricity network remains essential, but in practice it will take years. So there is a need for short-term solutions that can be integrated into long-term planning. We, the members of the TU Delft PowerWeb Institute, call on the government, network operators and regulator to explore the flexible backstop as an additional grid security measure,’ they said. The entire Paper can be read here . Kenneth Brunninx Associate Professor at the Faculty of Engineering, Governance and Management, where he uses quantitative models to evaluate energy policy and market design with the aim of reducing CO2 emissions. Simon Tindemans is Associate Professor in the Intelligent Electrical Power Grids group at Faculty of Electrical Engineering, Mathematics and Computer Science. His research interests include uncertainty and risk management for power grids. TU Delft PowerWeb Institute is a community of researchers who are investigating how to make renewable energy systems reliable, future proof and accessible to everyone.

Empowering professionals – vital for the longevity of any organisation

Empowering professionals – vital for the longevity of any organisation “Employers need to recognise that allowing employees to develop themselves is essential to business success, and space must be made for that,” says Willem van Valkenburg, Executive Director of TU Delft’s Extension School for Continuing Education. In a recent Topic Talks interview on New Business Radio , van Valkenburg highlighted the need for a robust learning culture within organisations to keep pace with an evolving job market and rapid technological advancements. Barriers to continous development Reflecting on the learning culture in the Netherlands, as an example, van Valkenburg pointed out an often-overlooked barrier: although resources for professional development exist, business needs frequently take precedence, sidelining employee growth. “Employers must actively create environments that encourage continuous learning and foster dialogue about upskilling and growth opportunities. This is especially crucial for companies struggling with unfilled vacancies. When staffing is low, the demand on existing employees intensifies, making it harder to prioritise time for learning.” Recognising these challenges, TU Delft has developed short-duration online courses to help professionals fit learning around their work responsibilities. The importance of up-to-date skills is clear: businesses need to adopt new technologies to remain competitive, yet they often face skills gaps that traditional training does not cover. Van Valkenburg shared an example of a professional who, after completing TU Delft’s AI in Manufacturing course, applied their learning to increase production by 50%. To address the need for specialised knowledge, TU Delft’s approach goes beyond standard coursework, fostering innovation through collaborative learning communities. “Our learning communities bring together researchers, professionals, and policymakers to collaboratively address real-world problems. This structure enables participants to learn while actively solving practical challenges,” explained van Valkenburg. Throughout the conversation, van Valkenburg emphasised the value of aligning academic expertise with industry needs. By integrating TU Delft’s research into their courses, participants have access to the latest advancements, keeping them at the forefront of their fields. “Our courses, accessible in English and designed for a global audience, allow professionals from diverse sectors to stay ahead of technological shifts,” he said. Tangible impact In addition to cutting-edge content, the Extension School maintains a learner-centred approach. Feedback is integral, helping TU Delft ensure its courses remain relevant and impactful. “What moves me the most are people in developing countries who say, ‘I took a course on solar energy. With the knowledge I gained, I wrote a project plan to install solar panels in our village. Now, we have more electricity and can develop ourselves further.'" Building lifelong learning at all levels is essential to creating a resilient workforce and a sustainable future. TU Delft’s Extension School is committed to keeping these conversations alive, empowering professionals worldwide to drive meaningful change. For those interested in hearing the full interview in Dutch, please click the link. Luister hier Support Willem van Valkenburg and our work by giving us a shout-out on LinkedIn linkedin