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JACIII Vol.28 No.1 pp. 21-28
doi: 10.20965/jaciii.2024.p0021
(2024)

Research Paper:

Application of Fuzzy Logic for Robotic Arm Joint Control of an Explosive Ordnance Disposal Unit

Arvin H. Fernando*,† ORCID Icon, Marielet A. Guillermo** ORCID Icon, Ronnie S. Concepcion II** ORCID Icon, Laurence A. Gan Lim* ORCID Icon, Edwin Sybingco*** ORCID Icon, Argel A. Bandala** ORCID Icon, Ryan Rhay P. Vicerra** ORCID Icon, and Elmer P. Dadios** ORCID Icon

*Department of Mechanical Engineering, De La Salle University
2401 Taft Avenue, Malate, Manila 1004, Philippines

Corresponding author

**Department of Manufacturing Engineering and Management, De La Salle University
2401 Taft Avenue, Malate, Manila 1004, Philippines

***Department of Electronics and Computer Engineering, De La Salle University
2401 Taft Avenue, Malate, Manila 1004, Philippines

Received:
March 3, 2023
Accepted:
July 14, 2023
Published:
January 20, 2024
Keywords:
EOD, fuzzy logic control, luffing, mobile jib crane, tip-over stability margin
Abstract

Precise luffing of payload in mobile cranes is a crucial part of material handling and safety in industrial operations. Explosive ordnance disposal uses a bomb disposal robot to safely disable explosive devices at a safe distance. This robot is a mobile jib crane type with a gripper as an end effector instead of the typical suspension cable with a hook. The common challenge of this crane type is the arm/jib movement sensitivity with respect to tip-over stability of the crane body. This is directly influenced by the payload and constrained by the degree of freedom. This paper presents a control strategy of the joint for luffing such that the back wheels remain in contact with the surface ground and avoid bucking at any given instance of weight change in the payload. Fuzzy logic was applied to control the motor torque and luffing angle of the arm in response to the load and gripper opening size to maintain the tip-over stability margin at the highest value possible. The response curves at different configurations of the two input signals were also analyzed based on the rules set to determine its precision with respect to the expected response curve.

Cite this article as:
A. Fernando, M. Guillermo, R. Concepcion II, L. Lim, E. Sybingco, A. Bandala, R. Vicerra, and E. Dadios, “Application of Fuzzy Logic for Robotic Arm Joint Control of an Explosive Ordnance Disposal Unit,” J. Adv. Comput. Intell. Intell. Inform., Vol.28 No.1, pp. 21-28, 2024.
Data files:
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Last updated on Feb. 19, 2024