We introduce Kinematic Kitbashing, an automatic framework that synthesizes functionality-aware articulated objects by reusing parts from existing models. Given a kinematic graph with a small collection of articulated parts, our optimizer jointly solves for the spatial placement of every part so that (i) attachments remain geometrically sound over the entire range of motion and (ii) the assembled object satisfies user-specified functional goals such as collision-free actuation, reachability, or trajectory following. At its core is a kinematics-aware attachment energy that aligns vector distance function features sampled across multiple articulation snapshots. We embed this attachment term within an annealed Riemannian Langevin dynamics sampler that treats functionality objectives as additional energies, enabling robust global exploration while accommodating non-differentiable functionality objectives and constraints. Our framework produces a wide spectrum of assembled articulated shapes, from trash-can wheels grafted onto car bodies to multi-segment lamps, gear-driven paddlers, and reconfigurable furniture, and delivers strong quantitative improvements over state-of-the-art baselines across geometric, kinematic, and functional metrics. By tightly coupling articulation-aware geometry matching with functionality-driven optimization, Kinematic Kitbashing bridges part-based shape modeling and functional assembly design, empowering rapid creation of interactive articulated assets.
翻译:我们提出运动学拼接,一种通过复用现有模型部件来合成功能感知铰接物体的自动化框架。给定包含少量铰接部件的运动学图,我们的优化器联合求解每个部件的空间布局,使得:(i) 附件在整个运动范围内保持几何合理性;(ii) 组装后的物体满足用户指定的功能目标,如无碰撞驱动、可达性或轨迹跟踪。其核心是运动学感知的附着能量函数,该函数对齐了在多个铰接快照中采样的向量距离函数特征。我们将此附着项嵌入退火黎曼朗之万动力学采样器中,将功能目标视为附加能量项,从而实现鲁棒的全局探索,同时适应不可微分的功能目标与约束。我们的框架可生成多种组装的铰接形状——从移植到车身的垃圾桶轮毂到多段式灯具、齿轮驱动划桨器和可重构家具,并在几何、运动学及功能指标上较现有先进基线实现显著定量提升。通过将铰接感知的几何匹配与功能驱动优化紧密结合,运动学拼接桥接了基于部件的形状建模与功能装配设计,赋能交互式铰接资产的快速创建。