1 citations · 2 across the 6 of their papers we have counts for
8 papers
Semantic SLAM in Precision Agriculture using Bayesian Inference
Ruben Beumer, Sander Doodeman, René van de Molengraft +1
This paper presents a real-time semantic world modeling framework specialized for precision agriculture using autonomous robots. The framework combines probabilistic mapping of obj…
Mechanical Precision Weeding with a Quadruped Robot
Ruben Beumer, Tom Janssen, René van de Molengraft +1
Herbicide-based weed control is increasingly unsustainable due to rising weed resistance and the adverse environmental impacts of chemical use. While mechanical weed control avoids…
Short-Horizon Position Accuracy of Single-Track Models: Implications for Motion Planning of Autonomous Vehicles
Aron J. Aertssen, Lars A. T. H. van Alen, Igo J. M. Besselink +2
Accurate and computationally efficient vehicle models are essential for motion planning of autonomous vehicles, where positional accuracy directly affects trajectory feasibility an…
SDS++: Online Situation-Aware Drivable Space Estimation for Automated Driving
Manuel Muñoz Sánchez, Gijs Trots, Robin Smit +4
Autonomous Vehicles (AVs) need an accurate and up-to-date representation of the environment for safe navigation. Traditional methods, which often rely on detailed environmental rep…
Generation of skill-specific maps from graph world models for robotic systems
Koen de Vos, Gijs van den Brandt, Jordy Senden +3
With the increase in the availability of Building Information Models (BIM) and (semi-) automatic tools to generate BIM from point clouds, we propose a world model architecture and…
Prediction Horizon Requirements for Automated Driving: Optimizing Safety, Comfort, and Efficiency
Manuel Muñoz Sánchez, Chris van der Ploeg, Robin Smit +3
Predicting the movement of other road users is beneficial for improving automated vehicle (AV) performance. However, the relationship between the time horizon associated with these…
Robustness Benchmark of Road User Trajectory Prediction Models for Automated Driving
Manuel Muñoz Sánchez, Emilia Silvas, Jos Elfring +1
Accurate and robust trajectory predictions of road users are needed to enable safe automated driving. To do this, machine learning models are often used, which can show erratic beh…
Linear Control of Time-Domain Constrained Systems
W. H. T. M. Aangenent, W. P. M. H. Heemels, M. J. G. Van De Molengraft +2
This paper presents a general framework for the design of linear controllers for linear systems subject to time-domain constraints. The design framework exploits sums-of-squares te…