Characterization and commissioning of a mobile robot platform for swarm-oriented applications
DOI:
https://doi.org/10.24054/rcta.v1i47.4152Keywords:
swarm robotics, autonomous navigation, mobile robotsAbstract
Accurate sensing and reliable control are essential for the effective operation of autonomous mobile robots, particularly in constrained environments where navigation errors and detection failures can significantly affect performance. This work presents the characterization and commissioning of a mobile robot platform as a foundational stage toward swarm-based inventory localization strategies. The onboard infrared, light, and acoustic sensors were experimentally evaluated to determine their operational ranges, environmental sensitivity, and detection reliability. A Proportional-Derivative controller was implemented and tuned to enhance trajectory stability, while light sensing calibration ensured robust operation under varying ambient illumination. Additionally, an acoustic detection mechanism was integrated to enable robot-to-robot detection without physical contact. Experimental results confirmed that thorough sensor characterization, combined with targeted control adjustments, improved navigation stability and detection robustness. These developments establish a solid technical basis for the subsequent implementation of swarm coordination and clustering behaviors in autonomous inventory localization applications.
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References
P. N. Hutapea and M. Siallagan, "Predictive Analysis for Inventory Management of Coconut Warehouse (Case Study: Banio Lahewa)," International Journal of Current Science Research and Review, vol. 06, no. 11, Nov. 2023, doi: 10.47191/ijcsrr/V6-i11-44.
N. S. Sandoval Carrero, N. M. Acevedo Quintana, and L. M. Santos Jaimes, "LINEAMIENTOS DESDE LA INDUSTRIA 4.0 A LA EDUCACION 4.0: CASO TECNOLOGIA IoT," Revista Colombiana de Tecnologias de Avanzada (RCTA), vol. 1, no. 39, pp. 81-92, Jul. 2023, doi: 10.24054/rcta.v1i39.1379.
A. A. Ali, R. A. Rashid, N. M. Abdikadir, A. A. Mohamed, and M. M. Ahmed, "IoT Based Warehouse Management System Leveraging On RFID and Cloud Platform Technologies," in 2024 IEEE International Conference on Advanced Telecommunication and Networking Technologies (ATNT), IEEE, Sep. 2024, pp. 1-4. doi: 10.1109/ATNT61688.2024.10719252.
V. Casamayor-Pujol, M. Morenza-Cinos, B. Gaston, and R. Pous, "Autonomous stock counting based on a stigmergic algorithm for multi-robot systems," Comput Ind, vol. 122, p. 103259, Nov. 2020, doi: 10.1016/j.compind.2020.103259.
M. Vogrin, M. Stefanec, and T. Schmickl, "Social Distancing in Robot Swarms: Modulating Exploitation and Exploration Without Signal Exchange," in 2020 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, Dec. 2020, pp. 2233-2240. doi: 10.1109/SSCI47803.2020.9308502.
T. Schmickl et al., "Get in touch: cooperative decision making based on robot-to-robot collisions," Auton Agent Multi Agent Syst, vol. 18, no. 1, pp. 133-155, Feb. 2009, doi: 10.1007/s10458-008-9058-5.
S. Kernbach, R. Thenius, O. Kernbach, and T. Schmickl, "Re-embodiment of Honeybee Aggregation Behavior in an Artificial Micro-Robotic System," Adaptive Behavior, vol. 17, no. 3, pp. 237-259, Jun. 2009, doi: 10.1177/1059712309104966.
L. Bayindir, "A review of swarm robotics tasks," Neurocomputing, vol. 172, pp. 292-321, Jan. 2016, doi: 10.1016/j.neucom.2015.05.116.
F. Arvin, A. E. Turgut, F. Bazyari, K. B. Arikan, N. Bellotto, and S. Yue, "Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method," Adaptive Behavior, vol. 22, no. 3, pp. 189-206, Jun. 2014, doi: 10.1177/1059712314528009.
M. Bodi, R. Thenius, T. Schmickl, and K. Crailsheim, "How Two Cooperating Robot Swarms Are Affected by Two Conflictive Aggregation Spots," 2011, pp. 367-374. doi: 10.1007/978-3-642-21314-4_46.
O. Acevedo, Y. Y. Rios, J. Duque, E. Gomez, and L. Garcia, "A Software for Simulating Robot Swarm Aggregation," 2022, pp. 386-399. doi: 10.1007/978-3-031-20611-5_32.
O. Acevedo, Y. Y. Rios, L. Garcia, and D. Narvaez, "A study of the Beeclust algorithm for robot swarm aggregation," in 2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT), IEEE, Dec. 2022, pp. 1-6. doi: 10.1109/ICMLANT56191.2022.9996514.
J.-M. Valin, F. Michaud, J. Rouat, and D. Letourneau, "Robust sound source localization using a microphone array on a mobile robot," in Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453), IEEE, pp. 1228-1233. doi: 10.1109/IROS.2003.1248813.
M. Itani, T. Chen, T. Yoshioka, and S. Gollakota, "Creating speech zones with self-distributing acoustic swarms," Nat Commun, vol. 14, no. 1, p. 5684, Sep. 2023, doi: 10.1038/s41467-023-40869-8.
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Copyright (c) 2026 Hernán David Sánchez Restrepo, Yennifer Yuliana Ríos Diaz, Ana Valentina Montañez Cuellar
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