Automatic Generation of Optimization Model using Process Mining and Petri Nets for Optimal Motion Planning of 6-DOF Manipulators
Takuma Bando, Tatsushi Nishi, Md Moktadir Alam, Ziang Liu, Tomofumi Fujiwara
Abstract
We propose an optimization system for motion planning of robot arms using Petri Nets. The proposed optimization system consists of four sub-systems consisting of automatic generation of Petri Nets from event log data, optimization system of firing sequence of derived Petri Net model, verification system using Petri Net simulation, and an automatic program generation system. The model generation system automatically generates the Petri Net model from the event logs using process mining. The Petri Net verification system is used to check the consistency of the generated Petri Nets to obtain the optimal firing sequence for robot motion. The motion planning algorithm generates motion programs for robots based on optimal firing sequences. The proposed optimization model is applied to a 6-DOF (Degree of Freedom) robot manipulator (Niryo Ned). Experimental results show that the proposed method achieves motion plan optimization for the pick-and-place operation with different robot configurations.
BibTeX
@inproceedings{iros2022_automaticgenerat,
title = {Automatic Generation of Optimization Model using Process Mining and Petri Nets for Optimal Motion Planning of 6-DOF Manipulators},
author = {Takuma Bando and Tatsushi Nishi and Md Moktadir Alam and Ziang Liu and Tomofumi Fujiwara},
booktitle = {IROS 2022},
year = {2022}
}