Tootfinder

A Genetic Algorithm Framework for Optimizing Three-Impulse Orbital Transfers with Poliastro Simulation
Phuc Hao Do, Tran Duc Le
https://arxiv.org/abs/2508.03466 https://

A Genetic Algorithm Framework for Optimizing Three-Impulse Orbital Transfers with Poliastro Simulation
Orbital maneuver planning is a critical aspect of mission design, aimed at minimizing propellant consumption, which is directly correlated with the total velocity change ($ΔV$). While analytical solutions like the Hohmann and Bi-elliptic transfers offer optimal strategies for specific cases, they lack the flexibility for more general optimization problems. This paper presents a computational framework that couples a Genetic Algorithm (GA) with the Poliastro orbital mechanics library to autonom…

Multi-CAP: A Multi-Robot Connectivity-Aware Hierarchical Coverage Path Planning Algorithm for Unknown Environments
Zongyuan Shen, Burhanuddin Shirose, Prasanna Sriganesh, Bhaskar Vundurthy, Howie Choset, Matthew Travers
https://arxiv.org/abs/2509.14941

Multi-CAP: A Multi-Robot Connectivity-Aware Hierarchical Coverage Path Planning Algorithm for Unknown Environments
Efficient coordination of multiple robots for coverage of large, unknown environments is a significant challenge that involves minimizing the total coverage path length while reducing inter-robot conflicts. In this paper, we introduce a Multi-robot Connectivity-Aware Planner (Multi-CAP), a hierarchical coverage path planning algorithm that facilitates multi-robot coordination through a novel connectivity-aware approach. The algorithm constructs and dynamically maintains an adjacency graph that …

Computing optimal policies for managing inventories with noisy observations
Eugene Feinberg, Jefferson Huang, Pavlo Kasyanov, Thomas O'Neill
https://arxiv.org/abs/2507.19765

Computing optimal policies for managing inventories with noisy observations
This paper implements the Deep Deterministic Policy Gradient (DDPG) algorithm for computing optimal policies for partially observable single-product periodic review inventory control problems with setup costs and backorders. The decision maker does not know the exact inventory level, but can obtain noise-corrupted observations of them. The goal is to maximize the expected total discounted costs incurred over a finite planning horizon. We also investigate the Gaussian version of this problem wit…

Transplant-Ready? Evaluating AI Lung Segmentation Models in Candidates with Severe Lung Disease
Jisoo Lee, Michael R. Harowicz, Yuwen Chen, Hanxue Gu, Isaac S. Alderete, Lin Li, Maciej A. Mazurowski, Matthew G. Hartwig
https://arxiv.org/abs/2509.15083

Transplant-Ready? Evaluating AI Lung Segmentation Models in Candidates with Severe Lung Disease
This study evaluates publicly available deep-learning based lung segmentation models in transplant-eligible patients to determine their performance across disease severity levels, pathology categories, and lung sides, and to identify limitations impacting their use in preoperative planning in lung transplantation. This retrospective study included 32 patients who underwent chest CT scans at Duke University Health System between 2017 and 2019 (total of 3,645 2D axial slices). Patients with stand…