TY - GEN
T1 - Automatic Generation of Optimization Model using Process Mining and Petri Nets for Optimal Motion Planning of 6-DOF Manipulators
AU - Bando, Takuma
AU - Nishi, Tatsushi
AU - Alam, Md Moktadir
AU - Liu, Ziang
AU - Fujiwara, Tomofumi
N1 - Funding Information:
ACKNOWLEDGMENT This research is subsidized by New Energy and Industrial Technology Development Organization (NEDO) under a project JPNP20016. This paper is one of the achievements of joint research with and is jointly owned copyrighted material of ROBOT Industrial Basic Technology Collaborative Innovation Partnership.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
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U2 - 10.1109/IROS47612.2022.9982201
DO - 10.1109/IROS47612.2022.9982201
M3 - Conference contribution
AN - SCOPUS:85146356238
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 11767
EP - 11772
BT - IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022
Y2 - 23 October 2022 through 27 October 2022
ER -