Publications

First-author journal articles第一作者期刊论文

1. TOG

   

   Field Optimization for Scalable and Distortion-Aware Process Planning in Hybrid Additive-Subtractive Manufacturing

   Yongxue Chen, Tao Liu, Aoran Lyu, Yu Jiang, Neelotpal Dutta, and Charlie C. L. Wang

   ACM Transactions on Graphics (SIGGRAPH Asia), Conditionally accepted , 2026

   Abs HTML Video Code Website

   This paper presents a field-based optimization method for process planning in hybrid manufacturing, where the goal is to determine a feasible and efficient sequence of additive and subtractive operations for fabricating a target shape. Existing approaches rely on deterministic or discretized formulations, which lead to unoptimized fabrication time and make planning sensitive to voxel resolution. They also do not explicitly account for distortion in intermediate structures formed during manufacturing. To address these limitations, we represent manufacturing states using continuous fields, which scale naturally to models with large dimensions and fine geometric features while enabling smoother fabrication sequences. Based on this representation, we formulate process planning as a numerical optimization problem under multiple objectives, including final shape conformance, intermediate structural strength, manufacturing time, self-supporting and collision-free. Experimental results show that our method can generate distortion-aware process plans on a variety of models while substantially reducing fabrication time through up to a 72.6% reduction in the volume of extra support.

2. TOG

   

   Can Any Model Be Fabricated? Inverse Operation Based Planning for Hybrid Additive-Subtractive Manufacturing

   Yongxue Chen, Tao Liu, Yuming Huang, Weiming Wang, Tianyu Zhang, Kun Qian, Zikang Shi, and Charlie C. L. Wang

   ACM Transactions on Graphics (SIGGRAPH Asia), 2025

   Abs arXiv HTML Video Code Website

   This paper presents a method for computing interleaved additive and subtractive manufacturing operations to fabricate models of arbitrary shapes. We solve the manufacturing planning problem by searching a sequence of inverse operations that progressively transform a target model into a null shape. Each inverse operation corresponds to either an additive or a subtractive step, ensuring both manufacturability and structural stability of intermediate shapes throughout the process. We theoretically prove that any model can be fabricated exactly using a sequence generated by our approach. To demonstrate the effectiveness of this method, we adopt a voxel-based implementation and develop a scalable algorithm that works on models represented by a large number of voxels. Our approach has been tested across a range of digital models and further validated through physical fabrication on a hybrid manufacturing system with automatic tool switching.

3. T-ASE

   

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

   Yongxue Chen, Tianyu Zhang, Yuming Huang, Tao Liu, and Charlie C. L. Wang

   IEEE Transactions on Automation Science and Engineering, 2025

   Abs arXiv HTML Video Code

   This paper presents a concurrent and scalable trajectory optimization method to improve the quality of robot-assisted manufacturing, simultaneously optimizing tool orientations, kinematic redundancy, and waypoint timing on toolpaths with numerous waypoints to enhance kinematic smoothness while respecting manufacturing constraints. A key distinction from existing work is that this method handles these three aspects together rather than separately. To manage toolpaths with large numbers of waypoints efficiently, the authors developed a decomposition-based numerical scheme to optimize the trajectory in an out-of-core manner, which can also run in parallel. The method’s effectiveness is validated through both simulations and physical experiments focused on robot-assisted additive manufacturing applications.

4. RCIM

   

   Toolpath Generation for Robotic Flank Milling via Smoothness and Stiffness Optimization

   Yongxue Chen, Yaoan Lu, and Ye Ding

   Robotics and Computer-Integrated Manufacturing, 2023

   Abs HTML

   Robotic flank milling has outstanding advantages in machining large-scale slender surfaces. Currently, the paths for this process are mainly generated by optimizing redundant robot degrees of freedom (DoFs) on the basis of conventional 5-axis flank milling paths. This two-step framework, however, does not enable optimal robot kinematic and dynamical performance compared to the direct generation of 6-DoF robot paths, limiting the machining efficiency and effectiveness. The paper presents an optimization method to directly generate a toolpath with six DoFs for robotic flank milling. Firstly, the kinematic model of the milling system and the representation of the 6-DoF toolpath are established. Then, the standard geometric error for flank milling that conforms to the geometric specification is defined, and an efficient algorithm based on conformal geometric algebra is proposed to solve it. The toolpath optimization model with toolpath smoothness and robot stiffness as objective functions is established. A sequential quadratic programming algorithm is proposed to solve this highly non-linear problem based on the lexicographic order of arrays. The simulations and experiments demonstrate that the proposed method has better efficiency, robustness, and effectiveness compared with the existing methods.

5. JMSE

   

   Posture Optimization in Robotic Flat-End Milling Based on Sequential Quadratic Programming

   Yongxue Chen and Ye Ding

   ASME Journal of Manufacturing Science and Engineering, 2023

   Abs HTML

   Robotic flat-end milling of complex surfaces offers advantages such as high flexibility and high machining efficiency. In the process of planning the toolpath based on the cutter contact path, the robot functional redundancy and the tool orientation need to be solved carefully. This paper takes the weighted sum of the machining width and the toolpath smoothness performance criterion as the objective function, establishing an optimization model considering joint limits and gouging avoidance, with an efficient algorithm based on sequential quadratic programming proposed to solve the problem.

6. CAD

   

   An Analytical Method for Corner Smoothing of Five-Axis Linear Paths Using Conformal Geometric Algebra

   Yongxue Chen, Pengsheng Huang, and Ye Ding

   Computer-Aided Design, 2022

   Abs HTML

   This paper proposes an analytical G3 continuous corner smoothing method based on conformal geometric algebra for five-axis machining, addressing the tangential discontinuity of linear path segments that reduces machining efficiency and accuracy. The toolpath is represented in six-dimensional Euclidean space based on the locations of the tooltip point and a tool axis point, and the path is smoothed by G3 continuous circle-based splines under the constraints of maximum deviation error tolerance using conformal transformations and circles in conformal geometric algebra. The proposed approach generates a smooth toolpath that passes through the discrete cutter locations given in the original linear segments analytically, with improved cycle time thanks to the small curvature and G3 continuity of the toolpath.

7. SCTS

   

   An Efficient Method for Collision-Free and Jerk-Constrained Trajectory Generation with Sparse Way-Points for a Flying Robot

   Yongxue Chen, Wei Dong, and Ye Ding

   Science China Technological Sciences, 2021

   Abs HTML

   This paper presents an efficient approach to plan jerk-constrained smooth trajectories passing through desired way-points with allowable accuracy for an autonomous quadrotor. The proposed approach can generate a C3 continuous collision-free trajectory that passes through the sparse desired way-points with allowable accuracy while guaranteeing the chord error, velocity, acceleration, and jerk constraints.

Co-authored journal articles合作作者期刊论文

1. TOG

   

   Co-Optimization of Structure and Manufacturable Semi-Continuous Layers for Laminated Composites

   Tao Liu, Aoran Lyu, Yongxue Chen, Y. Jiang, M. J. Petty, and Charlie C. L. Wang

   ACM Transactions on Graphics, 2026

   Abs HTML Video Website

   This paper proposes a field-driven optimization framework that jointly optimizes structural topology and manufacturable layers to enable the design and manufacturing of optimized composite structures using fabric plies.

2. CAD

   

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

   Neelotpal Dutta, Tianyu Zhang, Tao Liu, Yongxue Chen, and Charlie C. L. Wang

   Computer-Aided Design, 2026

   Abs arXiv HTML Video Website

   Existing curved-layer-based process planning methods for multi-axis manufacturing address collisions only indirectly and generate toolpaths in a post-processing step, leaving toolpath geometry uncontrolled during optimization. This paper presents an implicit neural field-based framework for multi-axis process planning that overcomes these limitations by embedding both layer generation and toolpath design within a single differentiable pipeline. Using sinusoidally activated neural networks to represent layers and toolpaths as implicit fields, the method enables direct evaluation of field values and derivatives at any spatial point, thereby allowing explicit collision avoidance and joint optimization of manufacturing layers and toolpaths. The authors further investigate how network hyperparameters and objective definitions influence singularity behavior and topology transitions, offering built-in mechanisms for regularization and stability control, and demonstrate the approach on examples in both additive and subtractive manufacturing.

3. RCIM

   

   Force-Based Adaptive Deposition in Multi-Axis Additive Manufacturing: Low Porosity for Enhanced Strength

   Yuming Huang, Renbo Su, Kun Qian, Tianyu Zhang, Yongxue Chen, Tao Liu, Guoxin Fang, Weiming Wang, and Charlie C. L. Wang

   Robotics and Computer-Integrated Manufacturing, 2026

   Abs HTML Video Website

   This paper presents a force-based adaptive deposition method for reducing porosity in filament-based multi-axis additive manufacturing. Porosity often arises in 3D printed structures with curved layers due to non-uniform layer thickness, unstable material extrusion, and significant curvature variations across different regions of a model. The closed-loop control approach dynamically adjusts the local material deposition rate by modulating the printer head motion in response to force feedback while maintaining a constant extrusion speed. Compared to purely geometry-based methods, the approach effectively reduces porosity, leading to a significant improvement in the mechanical strength of fabricated specimens, demonstrating up to 72.1% higher breaking force while maintaining comparable or even slightly reduced weights.

4. TOG

   

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

   Tao Liu, Tianyu Zhang, Yongxue Chen, Weiming Wang, Yu Jiang, Yuming Huang, and Charlie C. L. Wang

   ACM Transactions on Graphics, 2025

   Abs arXiv HTML Video Website

   We propose a neural network-based computational framework for the simultaneous optimization of structural topology, curved layers, and path orientations to achieve strong anisotropic strength in fiber-reinforced thermoplastic composites while ensuring manufacturability. Our framework employs three implicit neural fields to represent geometric shape, layer sequence, and fiber orientation. This enables the direct formulation of both design and manufacturability objectives, such as anisotropic strength, structural volume, machine motion control, layer curvature, and layer thickness, into an integrated and differentiable optimization process. Physical experiments demonstrate that the composites generated by our co-optimization method can achieve an improvement of up to 33.1% in failure loads compared to composites with sequentially optimized structures and manufacturing sequences.

5. CompB

   

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

   Tianyu Zhang, Tao Liu, Neelotpal Dutta, Yongxue Chen, Renbo Su, Zhizhou Zhang, Weiming Wang, and Charlie C. L. Wang

   Composites Part B, 2025

   Abs arXiv HTML Video Code

   While multi-axis 3D printing can align continuous fibers along principal stresses in continuous fiber-reinforced thermoplastic composites to enhance mechanical strength, existing methods have difficulty generating toolpaths with high fiber coverage. This is mainly due to the orientation consistency constraints imposed by vector-field-based methods and the turbulent stress fields around stress concentration regions. This paper addresses these challenges by introducing a 2-RoSy representation for computing the direction field, which is then converted into a periodic scalar field to generate partial iso-curves for fiber toolpaths with nearly equal hatching distance. The proposed method can achieve toolpath coverage between 87.5% and 90.6% by continuous fibers with 1.1 mm width. Specimens fabricated using these toolpaths show up to 84.6% improvement in failure load and 54.4% increase in stiffness compared to results obtained from multi-axis 3D printing with sparser fibers.

6. TOG

   

   Neural Slicer for Multi-Axis 3D Printing

   Tao Liu, Tianyu Zhang, Yongxue Chen, Yuming Huang, and Charlie C. L. Wang

   ACM Transactions on Graphics, 2024

   Abs arXiv HTML Video Code Website

   This paper introduces a novel neural network-based computational pipeline as a representation-agnostic slicer for multi-axis 3D printing that can work on models with diverse representations and intricate topology. The approach involves employing neural networks to establish a deformation mapping, defining a scalar field in the space surrounding an input model, and isosurfaces are subsequently extracted from this field to generate curved layers for 3D printing. Creating a differentiable pipeline enables optimization of the mapping through loss functions directly defined on the field gradients as the local printing directions. New loss functions have been introduced to meet the manufacturing objectives of support-free and strength reinforcement.

7. CAD

   

   Point Pair-Based Expression of Cutter Swept Envelopes in Five-Axis Milling

   Ye Ding and Yongxue Chen

   Computer-Aided Design, 2023

   Abs HTML

   This paper proposes an efficient method of formulating cutter swept envelopes in five-axis milling based on conformal geometric algebra. The surface of the rotary cutter is represented as a canal surface, as the envelope of a one-parameter family of spheres. The swept envelopes generated by the general rigid motion of the cutter can be regarded as a two-parameter family of spheres. With the help of the dual representations of spheres and planes in conformal space, a point pair-based expression of the swept envelopes is formulated analytically, which represents two surfaces uniformly. Using the present method, the swept surfaces of a conical cutter, a drum-shaped cutter, and a toroidal cutter are illustrated. As an application, two types of collision detection methods for 5-axis milling are presented based on the point pair-based envelope expression.