J.J. van Beers

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Dive into the research topics where J.J. van Beers is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets
Solanki, P., Vertovec, N., Schnitzer, Y., van Beers, J. J., de Visser, C. C. & Abate, A., 2025, Proceedings of the IEEE 64th Conference on Decision and Control (CDC 2025). IEEE, p. 3907-3912 6 p. (Proceedings of the IEEE Conference on Decision and Control).
Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review
A novel algorithmic approach to obtaining maneuverable control-invariant sets
Solanki, P., Van Beers, J. J., Jamshidnejad, A. & De Visser, C. C., 2024, 2024 IEEE International Conference on Robotics and Automation, ICRA 2024. IEEE, p. 9916-9922 7 p. (Proceedings - IEEE International Conference on Robotics and Automation).
Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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A novel metric for detecting quadrotor loss-of-control
Van Beers, J. J., Solanki, P. & De Visser, C. C., 2024, 2024 IEEE International Conference on Robotics and Automation, ICRA 2024. IEEE, p. 15570-15576 7 p. (Proceedings - IEEE International Conference on Robotics and Automation).
Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Open Access
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2 Downloads (Pure)
Loss-of-Control Prediction of a Quadcopter Using Recurrent Neural Networks
Altena, A., van Beers, J. J. & de Visser, C. C., 2023, In: Journal of Aerospace Information Systems (online). 20, 10, p. 648-659 12 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
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111 Downloads (Pure)
Peaking into the Black-box: Prediction Intervals Give Insight into Data-driven Quadrotor Model Reliability
van Beers, J. J. & de Visser, C. C., 2023, AIAA SciTech Forum 2023. 21 p. AIAA 2023-0125. (AIAA SciTech Forum and Exposition, 2023).
Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Open Access
File
2 Link opens in a new tab Citations (Scopus)

135 Downloads (Pure)

Raw data: GRIND simulations for ecological and control systems
van Beers, J. (Creator), Solanki, P. (Creator), de Visser, C. C. (Creator), van de Leemput, I. (Creator) & van Nes, E. (Creator), TU Delft - 4TU.ResearchData, 11 Mar 2026
DOI: 10.4121/84E4C69A-F32F-49AE-B389-FCFED7DBFE3B
Dataset/Software: Dataset
Raw data: Propeller damage induced quadrotor loss of control
van Beers, J. (Creator), Solanki, P. (Creator), Scheffer, M. (Creator), van de Leemput, I. (Creator), van Nes, E. (Creator) & de Visser, C. C. (Creator), TU Delft - 4TU.ResearchData, 11 Mar 2026
DOI: 10.4121/308D8C70-CC88-45FB-B16A-5BD80531BEEF
Dataset/Software: Dataset

J.J. van Beers

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Collaborations and top research areas from the last five years

Dive into details

Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets

A novel algorithmic approach to obtaining maneuverable control-invariant sets

A novel metric for detecting quadrotor loss-of-control

Loss-of-Control Prediction of a Quadcopter Using Recurrent Neural Networks

Peaking into the Black-box: Prediction Intervals Give Insight into Data-driven Quadrotor Model Reliability

Raw data: GRIND simulations for ecological and control systems

Raw data: Propeller damage induced quadrotor loss of control

J.J. van Beers

Fingerprint

Collaborations and top research areas from the last five years

Research output

Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets

A novel algorithmic approach to obtaining maneuverable control-invariant sets

A novel metric for detecting quadrotor loss-of-control

Loss-of-Control Prediction of a Quadcopter Using Recurrent Neural Networks

Peaking into the Black-box: Prediction Intervals Give Insight into Data-driven Quadrotor Model Reliability

Datasets

Raw data: GRIND simulations for ecological and control systems

Raw data: Propeller damage induced quadrotor loss of control