most citedLearning Based Toolpath Planner on Diverse Graphs for 3D Printing

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

cs.RO2025

Implicit Neural Field-Based Process Planning for Multi-Axis Manufacturing: Direct Control over Collision Avoidance and Toolpath Geometry

Neelotpal Dutta, Tianyu Zhang, Tao Liu +2

Existing curved-layer-based process planning methods for multi-axis manufacturing address collisions only indirectly and generate toolpaths in a post-processing step, leaving toolp…

cs.GR2025

Can any model be fabricated? Inverse operation based planning for hybrid additive-subtractive manufacturing

Yongxue Chen, Tao Liu, Yuming Huang +5

This paper presents a method for computing interleaved additive and subtractive manufacturing operations to fabricate models of arbitrary shapes. We solve the manufacturing plannin…

cs.LG2025

Neural Co-Optimization of Structural Topology, Manufacturable Layers, and Path Orientations for Fiber-Reinforced Composites

Tao Liu, Tianyu Zhang, Yongxue Chen +4

We propose a neural network-based computational framework for the simultaneous optimization of structural topology, curved layers, and path orientations to achieve strong anisotrop…

cs.GR2024

Toolpath Generation for High Density Spatial Fiber Printing Guided by Principal Stresses

Tianyu Zhang, Tao Liu, Neelotpal Dutta +5

While multi-axis 3D printing can align continuous fibers along principal stresses in continuous fiber-reinforced thermoplastic (CFRTP) composites to enhance mechanical strength, ex…

cs.RO2024

Co-Optimization of Tool Orientations, Kinematic Redundancy, and Waypoint Timing for Robot-Assisted Manufacturing

Yongxue Chen, Tianyu Zhang, Yuming Huang +2

In this paper, we present a concurrent and scalable trajectory optimization method to improve the quality of robot-assisted manufacturing. Our method simultaneously optimizes tool…

cs.RO20241 cited

Learning Based Toolpath Planner on Diverse Graphs for 3D Printing

Yuming Huang, Yuhu Guo, Renbo Su +9

This paper presents a learning based planner for computing optimized 3D printing toolpaths on prescribed graphs, the challenges of which include the varying graph structures on dif…