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Bounding Boxes as Goals: Language-Conditioned Grasping via Neuro-Symbolic Planning EquiDexFlow: Contact-Grounded SE(3)-Equivariant Dexterous Grasp Generative Flows FAWAM: Force-Aware World Action Models for Closed-Loop Contact-Rich Manipulation Planning with the Views via Scene Self-Exploration Lifted Schrödinger Bridges for Gaussian Mixture Endpoints: Projection Gaps and Path-Space Obstructions Micro-Swarm Locomotion Optimization in Dynamic Flow using Multi-Objective Multi-Agent Reinforcement Learning OGPO: Sample Efficient Full-Finetuning of Generative Control Policies BEVal: A Cross-dataset Evaluation Study of BEV Segmentation Models for Autonomous Driving Safe Bayesian Optimization for Complex Control Systems via Additive Gaussian Processes Learning Multi-Modal Whole-Body Control for Real-World Humanoid Robots SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge Latent Linear Quadratic Regulator for Robotic Control 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Space-Time Continuum: Continuous Shape and Time State Estimation for Flexible Robots
Spencer Teetaert, Sven Lilge, Jessica Burgner-Kahrs, Timothy D. · 2024-09-19 · via cs.RO updates on arXiv.org

This extended abstract introduces a novel method for continuous state estimation of continuum robots. We formulate the estimation problem as a factor-graph optimization problem using a novel Gaussian-process prior that is parameterized over both arclength and time. We use this to introduce the first continuous-time-and-space state estimation method for continuum robots.

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