Snap-Bounded and Time-Optimal Feedrate Scheduling for Robotic Milling of Complex Surface Parts With Analytical Solution

Abstract

Feedrate scheduling is crucial for improving productivity and accuracy in robotic milling applications. However, due to the nonlinear relationship between the joint space and task space, how to plan a time-optimal feedrate profile with quick analytical solution while ensuring kinematic control up to the snap level remains quite a challenge. To solve these concerns, a snap-bounded and time-optimal feedrate scheduling model is first presented in this article. For accelerating the solving process of the nonlinear model, a synchronous linearization approach is also introduced to help relax the highly nonlinear constraints in both joint space and task space into linear ones. Thereby, the originally complex feedrate scheduling issue is converted to a finite-state convex optimization problem, and an analytical solution to the feedrate profile could be computed efficiently using a straightforward linear programming algorithm. Finally, comparative simulation and experiment are carried out to verify the effectiveness of the proposed method.