Tootfinder

A Bi-Level Optimization Method for Redundant Dual-Arm Minimum Time Problems
Jonathan Fried, Santiago Paternain
https://arxiv.org/abs/2506.03982 https://

A Bi-Level Optimization Method for Redundant Dual-Arm Minimum Time Problems
In this work, we present a method for minimizing the time required for a redundant dual-arm robot to follow a desired relative Cartesian path at constant path speed by optimizing its joint trajectories, subject to position, velocity, and acceleration limits. The problem is reformulated as a bi-level optimization whose lower level is a convex, closed-form subproblem that maximizes path speed for a fixed trajectory, while the upper level updates the trajectory using a single-chain kinematic formu…

This https://arxiv.org/abs/2412.09433 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCC_…

Solving Multiagent Path Finding on Highly Centralized Networks
The Mutliagent Path Finding (MAPF) problem consists of identifying the trajectories that a set of agents should follow inside a given network in order to reach their desired destinations as soon as possible, but without colliding with each other. We aim to minimize the maximum time any agent takes to reach their goal, ensuring optimal path length. In this work, we complement a recent thread of results that aim to systematically study the algorithmic behavior of this problem, through the paramet…

Laser Scan Path Design for Controlled Microstructure in Additive Manufacturing with Integrated Reduced-Order Phase-Field Modeling and Deep Reinforcement Learning
Augustine Twumasi, Prokash Chandra Roy, Zixun Li, Soumya Shouvik Bhattacharjee, Zhengtao Gan
https://arxiv.org/abs/2506.21815 …

Laser Scan Path Design for Controlled Microstructure in Additive Manufacturing with Integrated Reduced-Order Phase-Field Modeling and Deep Reinforcement Learning
Laser powder bed fusion (L-PBF) is a widely recognized additive manufacturing technology for producing intricate metal components with exceptional accuracy. A key challenge in L-PBF is the formation of complex microstructures affecting product quality. We propose a physics-guided, machine-learning approach to optimize scan paths for desired microstructure outcomes, such as equiaxed grains. We utilized a phase-field method (PFM) to model crystalline grain structure evolution. To reduce computati…