Jan Swevers

Shamil Mamedov, A. René Geist, Jan Swevers et al.

Accurately predicting deformable linear object (DLO) dynamics is challenging, especially when the task requires a model that is both human-interpretable and computationally efficient. In this work, we draw inspiration from the pseudo-rigid body method (PRB) and model a DLO as a serial chain of rigid bodies whose internal state is unrolled through time by a dynamics network. This dynamics network is trained jointly with a physics-informed encoder that maps observed motion variables to the DLO's hidden state. To encourage the state to acquire a physically meaningful representation, we leverage the forward kinematics of the PRB model as a decoder. We demonstrate in robot experiments that the proposed DLO dynamics model provides physically interpretable predictions from partial observations while being on par with black-box models regarding prediction accuracy. The project code is available at: http://tinyurl.com/prb-networks

Yan-Yun Zhang, Jef Billet, Jan Swevers et al.

RTK augmentation andINS integration are widely used to improve GNSS positioning performance. However, on inland waterways, bridges and surrounding structures can degrade satellite visibility and correction availability, causing RTK augmentation loss, and GNSS/INS fusion transients. Since these effects depend on the local environment and sensor configuration, nominal receiver specifications are insufficient, and deployment-specific characterization is required. This paper presents a benchmarking study of an AsteRx-i3 D Pro+ GNSS/INS receiver installed within the mobile Sensor Box developed at KU Leuven. The study combines a real-world bridge-passage case study, static benchmarking, and closed-loop path-following experiments. The static benchmarking evaluates four receiver configurations: standalone GNSS, standalone GNSS with INS integration, RTK-augmented GNSS, and RTK-augmented GNSS with INS integration. The closed-loop experiments use INS-integrated GNSS as the navigation input and compare path-following operational performance with and without RTK augmentation. Results show that correction loss during bridge passage causes reduced positioning accuracy, increased positioning uncertainty and recovery-induced state jumps exceeding 1 m. Static benchmarking and closed-loop experiments confirm that RTK augmentation substantially improves positioning precision and uncertainty consistency, while INS integration supports short-term continuity during RTK unavailability but may introduce drift, bias, or transient uncertainty variations. By characterizing the deployment-specific receiver behavior with RTK augmentation and INS integration, this study motivates higher-level state estimation as a necessary next step toward spatially continuous and uncertainty-consistent positioning on inland waterway. The experimental data are released at: https://doi.org/10.5281/zenodo.20541733.