1 citations · 2 across the 6 of their papers we have counts for
6 papers · 1 filter
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…