联合优化机器人巡检路径与姿态配置,实现更高效无碰撞的检测。
Coupled Routing and Configuration Optimization for Multi-Viewpoint Robotic Inspection

- 将路径顺序与每个视角的姿态配置一起全局优化
- 相比传统方法,端到端检测时间减少30%以上
- 适合需要快速精准巡检的工业机器人场景
我们提出一种统一框架,将一组6-自由度的巡检视角转化为9-自由度机器人系统的最优时间、无碰撞路径。不同于固定每个视角单一逆运动学配置的模块化流程,本方法在单个全局搜索中联合优化访问顺序与各视角配置。每个视角的三维自运动流形以闭式形式参数化,确保位姿约束自然满足;全程时间近似采用闭式可接受的双积分器代理模型;巡检路线通过随机键编码。使用无导数优化器(CMA-ES)最小化廉价惩罚目标,之后仅对选定路径边进行直接配点轨迹优化,验证动态可行性与力矩限制并返回精确时序。该方法将轨迹求解复杂度从视点数的平方级降至线性级,消除了模块化流程中解耦导致的非全局最优问题。仿真与真实机器人实验(基于KUKA LBR iiwa带2-自由度直线模组)验证了方法的可行性、平滑执行性及相较模块化和距离基线的端到端时间降低效果。
原文摘要 · Abstract (English)
We present a unified framework that turns a set of 6-DoF inspection viewpoints into a time-optimal, collision-free route for a 9-DoF robotic system. Unlike modular pipelines that fix a single inverse-kinematics (IK) configuration per viewpoint, build an all-pairs travel-time map, and then route, our method jointly optimizes the visiting order and the per-viewpoint configuration in a single global search. The three-dimensional self-motion manifold of each viewpoint is parameterized in closed form so that the pose constraint holds by construction, the rest-to-rest travel time is approximated by a closed-form admissible double-integrator surrogate, and the tour is encoded by random keys. A derivative-free optimizer (CMA-ES) minimizes a cheap penalized objective over order and configuration, after which direct-collocation trajectory optimization is applied only to the edges of the selected route to certify dynamic feasibility and torque limits, and to return exact timings. This reduces the trajectory solves from quadratic to linear in the number of viewpoints and removes the decoupling that prevents modular pipelines from being globally time-optimal. Simulations and real-robot experiments on a KUKA LBR iiwa with a 2-DoF linear stage validate feasibility, smooth execution, and reduced end-to-end inspection time relative to modular and naive distance-based baselines.
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