Tim-David Job — accepted AI-conference papers

2024

Physics-Informed Neural Networks for Continuum Robots: Towards Fast Approximation of Static Cosserat Rod Theory

Martin Bensch, Tim-David Job, Tim-Lukas Habich, Thomas Seel, Moritz Schappler

ICRA 2024poster

Sophisticated models can accurately describe deformations of continuum robots while being computationally demanding, which limits their application. Especially when considering sampling-based path planning, the model has to be evaluated frequently, which can lead to substantially increased computati…

Cited by 4 Source ↗Scholar ↗

2023

Multiple-Contact Estimation for Tendon-Driven Continuum Robots with Proprioceptive Sensor Information by Contact Particle Filter and Kinetostatic Models

Tim-David Job, Martin Bensch, Moritz Schappler

IROS 2023poster

This paper presents a new approach to determine single and multiple simultaneous contact forces on a tendon-driven continuum robot (CR). The estimation is based solely on the proprioceptive tendon force and length sensors that are already present. Unlike for rigid-body robots, only indirect measurem…

Cited by 1 Source ↗Scholar ↗