Coupled Routing and Configuration Optimization for Multi-Viewpoint Robotic Inspection

2026-06-17

AI Summary

This work addresses the suboptimality in global execution time arising from the decoupling of path planning and joint configuration in multi-view robotic inspection. To overcome this limitation, the authors propose a unified optimization framework that jointly determines the visiting sequence of multiple 6-DoF inspection poses and the corresponding inverse kinematics solutions for a 9-DoF robot. By co-optimizing the visitation order and joint configurations on the three-dimensional self-motion manifold, the approach circumvents the inherent suboptimality of conventional modular pipelines and reduces trajectory computation complexity from quadratic to linear. The method integrates closed-form parameterization of the self-motion manifold, a double-integrator proxy model, random-key encoding, gradient-free CMA-ES optimization, and edge-wise direct collocation. Experiments on a KUKA LBR iiwa robot demonstrate that the generated trajectories are collision-free, smooth, and time-optimal, achieving significantly shorter end-to-end inspection times compared to modular and distance-based baselines.

Abstract

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.

Problem

• robotic inspection
• time-optimal routing
• collision-free path planning
• multi-viewpoint optimization
• configuration selection

Innovation

• joint optimization
• self-motion manifold
• time-optimal routing
• derivative-free optimization
• direct collocation