Performansi Navigasi Robot Leader-Follower menggunakan Algoritma Logika Fuzzy Interval Tipe 2

  • Gita Fadila Fitriana Institut Teknologi Telkom Purwokerto
  • Rifki Adhitama Institut Teknologi Telkom Purwokerto
Keywords: robot leader follower, Algoritma Logika Fuzzy Interval Tipe 2, navigasi robot, Algoritma Logika Fuzzy Tipe 1


A leader-follower robot is used to perform different tasks without continuous human assistance. The movement of robot leader-follower to environment who do not structure, avoid persecution and achieving goals is very difficult. Related to the problem, the robot leader-follower requires navigating robots independently using Interval Fuzzy Logic Type-2 (IFLT) 2 Algorithm. The IFLT 2 algorithm performance is successfully applied to this leader-follower robot, with 8 base rules less than the Fuzzy Logic Type 1 Algorithm. This simulation, the robot successfully moves to avoid obstacles and go hand in hand with the position of the follower robot always following the position of the robot leader.


Download data is not yet available.


A. Saffiotti, “The uses of fuzzy logic in autonomous robot navigation,” vol. 1, 1997.

C. Wagner and H. Hagras, “A Genetic Algorithm Based Architecture for Evolving Type-2 Fuzzy Logic Controllers for Real World Autonomous Mobile Robots,” 2007 IEEE Int. Fuzzy Syst. Conf., pp. 1–6, 2007.

Z. Li and X. Liu, “Distributed Tracking Control for Linear Multiagent Systems With a Leader of Bounded Unknown Input,” vol. 58, no. 2, pp. 518–523, 2013.

S. K. Hussein and M. A. Al-Mutairi, “A Novel Prototype Model for Swarm Mobile Robot Navigation Based Fuzzy Logic Controller,” Int. J. Comput. Sci. Inf. Technol., vol. 11, no. 02, pp. 63–77, 2019.

G. F. Fitriana and S. Nurmaini, “Interval Type 2 Fuzzy Logic Algorithm for Leader-Follower Robot.”

T. Balch, R. C. Arkin, and S. Member, “Behavior-Based Formation Control for Multirobot Teams,” IEEE Trans. Robot. Autom., vol. 14, no. 6, pp. 926–939, 1998.

J. R. T. Lawton, R. W. Beard, and B. J. Young, “A decentralized approach to formation maneuvers,” IEEE Trans. Robot. Autom., vol. 19, no. 6, pp. 933–941, 2003.

A. Brunete, M. Hernando, E. Gambao, and J. E. Torres, “A behaviour-based control architecture for heterogeneous modular ,” Rob. Auton. Syst., vol. 60, pp. 1607–1624, 2012.

K. Tan and M. A. Lewis, “Virtual Structures for High-Precision Cooperative Mobile Robotic Control *,” Proc IROS 96 IEEE, pp. 132–139, 1996.

M. A. Lewis and K. Tan, “High Precision Formation Control of Mobile Robots Using Virtual Structures,” Auton. Robot. 4, vol. 403, pp. 387–403, 1997.

J. P. Desai, J. P. Ostrowski, and V. Kumar, “Modeling and control of formations of nonholonomic mobile robots,” Robot. Autom. IEEE Trans., vol. 17, no. 6, pp. 905–908, 2001.

J. L. Whittington and R. G. Bell, “Leader – member exchange , enriched jobs , and goal-setting : Applying fuzzy set methodology,” J. Bus. Res., vol. 69, no. 4, pp. 1401–1406, 2016.

J. D. McLurkin, “Analysis and Implementation of Distributed Algorithms for Multi-Robot Systems,” Theses Diss., 2008.

P. Chandak, “Study and Implementation of ‘ Follow the Leader,” 2002.

B. Tutuko, S. Nurmaini, Saparudin, and G. F. Fitriana, “Enhancement of Non-Holonomic leader-follower formation using Interval Type-2 Fuzzy Logic Controller,” Int. J. Online Eng., vol. 14, no. 9, pp. 124–142, 2018.

L. Hakim and V. Yonatan, “Deteksi Kebocoran Gas LPG menggunakan Detektor Arduino dengan algoritma Fuzzy Logic Mandani,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 1, no. 2, p. 114, 2017.

Q. Liang and J. M. Mendel, “Interval Type-2 Fuzzy Logic Systems : Theory and Design,” IEEE Trans. Fuzzy Syst., vol. 8, no. 5 october, pp. 535–550, 2000.

N. H. Seng, “Implementation of Various Types of Fuzzy Controls on a Mobile Robot Using Sonar Sensors,” 2008.

How to Cite
Fitriana, G. F., & Rifki Adhitama. (2019). Performansi Navigasi Robot Leader-Follower menggunakan Algoritma Logika Fuzzy Interval Tipe 2. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 3(3), 371 - 376.
Information Technology Articles