Tootfinder

Multi-robot Rigid Formation Navigation via Synchronous Motion and Discrete-time Communication-Control Optimization
Qun Yang, Soung Chang Liew
https://arxiv.org/abs/2510.02624 ht…

Multi-robot Rigid Formation Navigation via Synchronous Motion and Discrete-time Communication-Control Optimization
Rigid-formation navigation of multiple robots is essential for applications such as cooperative transportation. This process involves a team of collaborative robots maintaining a predefined geometric configuration, such as a square, while in motion. For untethered collaborative motion, inter-robot communication must be conducted through a wireless network. Notably, few existing works offer a comprehensive solution for multi-robot formation navigation executable on microprocessor platforms via w…

Observational Constraints on Evolution of Dust Disc Properties in Upper Scorpius
Paola Pinilla, Anibal Sierra, Nicolas T. Kurtovic, Rossella Anania, Sean Andrews, John Carpenter, Osmar Guerra-Alvarado, Feng Long, Sebastian Marino, Miguel Vioque, Ke Zhang
https://arxiv.org/abs/2509.19442

Observational Constraints on Evolution of Dust Disc Properties in Upper Scorpius
Protoplanetary discs in the Upper Scorpius star-forming region are excellent laboratories to investigate late stages of planet formation. In this work, we analyse the morphology of the dust continuum emission of 121 discs from an ALMA Band 7 survey of the Upper Scorpius region. This analysis is done in the visibility plane, to measure the flux, geometry and characterise potential structures. We compare the results with state-of-the art gas and dust evolution models that include external photoev…

KeySG: Hierarchical Keyframe-Based 3D Scene Graphs
Abdelrhman Werby, Dennis Rotondi, Fabio Scaparro, Kai O. Arras
https://arxiv.org/abs/2510.01049 https://…

KeySG: Hierarchical Keyframe-Based 3D Scene Graphs
In recent years, 3D scene graphs have emerged as a powerful world representation, offering both geometric accuracy and semantic richness. Combining 3D scene graphs with large language models enables robots to reason, plan, and navigate in complex human-centered environments. However, current approaches for constructing 3D scene graphs are semantically limited to a predefined set of relationships, and their serialization in large environments can easily exceed an LLM's context window. We introdu…

Joint Neural SDF Reconstruction and Semantic Segmentation for CAD Models
Shen Fan, Przemyslaw Musialski
https://arxiv.org/abs/2510.03837 https://arxiv.org/…

Joint Neural SDF Reconstruction and Semantic Segmentation for CAD Models
We propose a simple, data-efficient pipeline that augments an implicit reconstruction network based on neural SDF-based CAD parts with a part-segmentation head trained under PartField-generated supervision. Unlike methods tied to fixed taxonomies, our model accepts meshes with any number of parts and produces coherent, geometry-aligned labels in a single pass. We evaluate on randomly sampled CAD meshes from the ABC dataset with intentionally varied part cardinalities, including over-segmented s…

Sharp Large Deviations and Gibbs Conditioning for Threshold Models in Portfolio Credit Risk
Fengnan Deng, Anand N. Vidyashankar, Jeffrey F. Collamore
https://arxiv.org/abs/2509.19151

Sharp Large Deviations and Gibbs Conditioning for Threshold Models in Portfolio Credit Risk
We obtain sharp large deviation estimates for exceedance probabilities in dependent triangular array threshold models with a diverging number of latent factors. The prefactors quantify how latent-factor dependence and tail geometry enter at leading order, yielding three regimes: Gaussian or exponential-power tails produce polylogarithmic refinements of the Bahadur-Rao $n^{-1/2}$ law; regularly varying tails yield index-driven polynomial scaling; and bounded-support (endpoint) cases lead to an $…