Projects
Hybrid Additive-Subtractive Manufacturing增减材复合制造过程规划
Scalable and Distortion-Aware Field Optimization for Hybrid Manufacturing面向复合制造的可扩展且考虑变形的场优化
The framework uses continuous neural fields to determine fabrication sequences, support material, and tool configurations while jointly optimizing shape conformance, fabrication time, and intermediate-structure distortion under manufacturing constraints. It scales to large models, preserves fine features, reduces unnecessary support, and improves toolpath smoothness.
该框架利用连续神经场，在制造约束下确定制造序列、支撑材料与刀具配置，同时联合优化形状一致性、制造时间和中间结构变形。其可扩展至大型模型，能够保留精细特征、减少不必要的支撑，并提高刀具路径的平滑性。
Inverse Operation-Based Planning for Hybrid Manufacturing面向复合制造的逆向操作规划
The planner searches for inverse operations that progressively transform a target model into a null shape. Each operation defines an AM or SM step while preserving the manufacturability and structural stability of intermediate shapes. We theoretically prove that our method can automatically fabricate any shape exactly.
该规划方法通过搜索一系列逆向操作，将目标模型逐步转化为空形。每个逆向操作对应一个增材制造（AM）或减材制造（SM）步骤，并保证中间结构的可制造性与稳定性。我们从理论上证明，该方法可以自动、精确地制造任意形状。
Trajectory Co-Optimization for Robot-Assisted Manufacturing面向机器人辅助制造的轨迹协同优化
Scalable and Concurrent Trajectory Planning for Robot-Assisted Manufacturing面向机器人辅助制造的可扩展轨迹协同规划
The framework concurrently plans tool orientations, kinematic redundancy, and waypoint timing to improve kinematic smoothness under manufacturing constraints. A scalable decomposition improves computational efficiency for long toolpaths. It supports AM and SM processes in single- and multi-robot systems.
该框架协同规划工具姿态、运动学冗余自由度和路径点时间，在满足制造约束的同时改善运动学平滑性。可扩展的分解方法提升长路径的计算效率。该方法适用于 AM 与 SM 工艺中的单机器人和多机器人系统。
6-DoF Toolpath Planning for Robotic Flank Milling机器人侧铣的六自由度刀具路径规划
The method directly plans 6-DoF robotic flank-milling toolpaths instead of optimizing robot redundancy after conventional five-axis planning. Conformal geometric algebra evaluates machining error, while lexicographic sequential quadratic programming jointly improves toolpath smoothness and robot stiffness, yielding greater efficiency, robustness, and machining performance.
该方法直接规划机器人侧铣的六自由度刀具路径，取代在传统五轴路径基础上再优化机器人冗余自由度的两阶段方法。利用共形几何代数计算加工误差，并采用基于数组字典序的序列二次规划联合改善路径平滑性与机器人刚度，从而提升效率、鲁棒性和加工性能。
Tool Orientation and Redundancy Co-Optimization for Robotic Flat-End Milling机器人平底刀铣削的刀具姿态与冗余协同优化
The method concurrently plans tool orientation and robot functional redundancy for robotic flat-end milling. Sequential quadratic programming balances machining width and toolpath smoothness while enforcing joint limits and gouging avoidance, producing feasible, smooth postures for complex-surface machining.
该方法面向机器人平底刀铣削，协同规划刀具姿态与机器人功能冗余自由度。采用序列二次规划平衡加工宽度和刀具路径平滑性，同时满足关节限位与过切避免约束，为复杂曲面加工生成可行且平滑的机器人位姿。
Geometric Algebra for Manufacturing Geometry基于几何代数的加工几何建模
Analytical G³ Corner Smoothing for Five-Axis Toolpaths五轴刀具路径的解析 G³ 转角光顺
The method uses conformal geometric algebra to construct analytical G³-continuous, circle-based spline transitions for five-axis linear toolpaths while directly enforcing maximum deviation error. A six-dimensional representation couples tooltip positions and tool-axis directions, producing smooth paths with lower curvature and shorter machining cycle times.
该方法利用共形几何代数，为五轴线性刀具路径构造解析的 G³ 连续圆弧样条过渡，并直接约束最大偏差误差。通过六维表示耦合刀尖位置与刀轴方向，生成曲率更小、加工周期更短的平滑路径。
Point-Pair Modeling of Cutter Swept Envelopes基于点对的刀具扫掠包络面建模
The method represents rotary cutters as canal surfaces and uses conformal geometric algebra to derive a unified analytical point-pair expression for their swept envelopes under general rigid motion. It handles conical, drum-shaped, and toroidal cutters and supports efficient collision detection for five-axis milling.
该方法将回转刀具表示为管道面，并利用共形几何代数推导刀具在一般刚体运动下扫掠包络面的统一点对解析表达。该模型适用于锥形、鼓形与环形刀具，并支持五轴铣削中的高效碰撞检测。
Aerial Robot Trajectory Planning无人机轨迹规划
Efficient Collision-Free and Jerk-Constrained Trajectory Planning for Aerial Robots面向空中机器人的高效无碰撞跃度约束轨迹规划
The method efficiently combines C³-continuous path planning through sparse waypoints with jerk-constrained velocity planning. It jointly enforces chord-error, collision-avoidance, velocity, acceleration, and jerk constraints, producing dynamically smooth trajectories through cluttered environments.
该方法高效地结合了基于稀疏路点的 C³ 连续路径规划与跃度约束速度规划。通过联合满足弦误差、避障、速度、加速度与跃度约束，为复杂环境生成动力学平滑的飞行轨迹。