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A Novel Boustrophedon-Based Coverage Algorithm for Industrial Cleaning Robots: Performance Improvements and Implementation

Year 2025, Volume: 25 Issue: 2, 329 - 340

Eylül Özer , A. Burak İnner

Abstract

Industrial cleaning robots are used in large and complex environments, especially in factories and large retail spaces. It is critical for these robots to operate effectively without hitting or approaching obstacles. The boustrophedon coverage-based full coverage path planning algorithm is frequently preferred in industrial applications because it enables robots to scan an area completely and regularly. In this study, a customized boustrophedon coverage-based path planning algorithm is presented on the Robot Operating System (ROS) platform. The proposed algorithm optimizes the robot's movement area by using a parametric inflation radius instead of a safety margin compared to the classical boustrophedon algorithm. This method allows the robot to cover the area more efficiently without approaching obstacles. In the tests performed, the proposed algorithm achieved a higher coverage rate of 98.2% compared to the classical boustrophedon algorithm, while reducing the number of turns by 61%. Significant improvements were also observed in performance metrics such as travel time and path length. In the tests, the calculation time was measured as 44 seconds and the path tracking time as 101 seconds. The total distance covered by the robot is 19.43 meters and the rotation amount is determined as 19.56 radians. These results show that the proposed algorithm can work with higher coverage rate in both obstacle and unobstructed environments in a shorter time. The algorithm offers a significant development for industrial cleaning robots and stands out as an effective solution in large-scale applications.

Keywords

coverage path planning cellular decomposition full path coverage

References

  • An, V., Qu, Z., Crosby, F., Roberts, R., & An, V. (2020). A Triangulation-Based Coverage Path Planning. IEEE Transactions on Automation Science and Engineering, 15(4), 1653-1662. https://doi.org/10.1109/TASE.2018.2799927
  • Bähnemann, R., Lawrance, N., Chung, J. J., Pantic, M., Siegwart, R., & Nieto, J. (2021). Revisiting Boustrophedon Coverage Path Planning as a Generalized Traveling Salesman Problem. In J. M. R. Sivalingam, J. A. Movellan, & S. Ozawa (Eds.), Field and Service Robotics (pp. 237-252). Springer. https://doi.org/10.1007/978-981-15-9460-1_20
  • Beşkirli, M. and Tefek, M. (2019). Parçacık sürü optimizasyon algoritması kullanılarak optimum robot yolu planlama. European Journal of Science and Technology, 201-213. https://doi.org/10.31590/ejosat.637832
  • Bobkov, D., Kiechle, M., Hilsenbeck, S., & Steinbach, E. (2017). Room Segmentation in 3D Point Clouds Using Anisotropic Potential Fields. 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 1-6. https://doi.org/10.1109/ICCIC.2017.8524392
  • Bormann, R., Jordan, F., Hampp, J., & Hagele, M. (2018). Indoor Coverage Path Planning: Survey, Implementation, Analysis. 2018 IEEE International Conference on Robotics and Automation (ICRA), 1718-1725. https://doi.org/10.1109/ICRA.2018.8460566
  • Cai, Z., Li, S., Gan, Y., Zhang, R., & Zhang, Q. (2022). Research on Complete Coverage Path Planning Algorithms Based on A* Algorithms. Expert Systems with Applications, 207, 117738. https://doi.org/10.1016/j.eswa.2022.117738
  • Carvalho, J. P., & Aguiar, A. P. (2023). A Reinforcement Learning Based Online Coverage Path Planning Algorithm. IEEE Transactions on Automation Science and Engineering, 20(3), 1459-1471. https://doi.org/10.1109/TASE.2023.3272003
  • Chen, X., Tucker, T. M., Kurfess, T. R., & Vuduc, R. (2019). Adaptive Deep Path: Efficient Coverage of a Known Environment Under Various Configurations. IEEE Robotics and Automation Letters, 5(2), 1816-1823. https://doi.org/10.1109/LRA.2020.2966891
  • Choi, Y.-H., Lee, T.-K., Baek, S.-H., & Oh, S.-Y. (2009). Online Complete Coverage Path Planning for Mobile Robots Based on Linked Spiral Paths Using Constrained Inverse Distance Transform. Journal of Intelligent & Robotic Systems, 56(4), 539-555. https://doi.org/10.1007/s10846-009-9310-2
  • Chowdhury, J. C., & Prabhakar, P. (2023). Optimal Multi-Robot Coverage Path Planning for Agricultural Fields using Motion Dynamics. IEEE Access, 11, 76679-76689. https://doi.org/10.1109/ACCESS.2023.3289267
  • Dakulović, M., Horvatić, S., & Petrović, I. (2011). Complete Coverage D* Algorithm for Path Planning of a Floor-Cleaning Mobile Robot. IFAC Proceedings Volumes, 44(1), 11939-11944. https://doi.org/10.3182/20110828-6-IT1002.03306
  • Dönmez, E. and Kocamaz, A. (2019). Çoklu hedeflerin çoklu robotlara paylaştırılması için bir yük dengeleme sistemi. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 8(2), 533-548. https://doi.org/10.17798/bitlisfen.467757
  • Esfahani, M. A., Wang, H., Wu, K., & Yuan, S. (2020). Unsupervised Scene Categorization, Path Segmentation. IEEE Transactions on Intelligent Transportation Systems, 22(12), 7601-7613. https://doi.org/10.1109/TITS.2020.3034683
  • Gajjar, S., Bhadani, J., Dutta, P., & Rastogi, N. (2017). Complete Coverage Path Planning Algorithm for Known 2D Environment. 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 1-5. https://doi.org/10.1109/ICCIC.2017.8524392
  • Gezer, A. (2024). Parçalı hücresel genetik algoritma ile insansız hava aracı performansına dayalı yol planlama. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi. 40 (1), 135 - 154 https://doi.org/10.17341/gazimmfd.1156817
  • Guo, S., Wang, T., Huang, Y., & You, D. (2022). Path planning algorithm for sweeping robot full traversal cleaning area. IEEE Access, 10, 119273-119283. https://doi.org/10.1109/ACCESS.2022.3221437
  • Kleiner, A., Baravalle, R., Kolling, A., Pilotti, P., & Munich, M. (2017). A Solution to Room-by-Room Coverage for Autonomous Cleaning Robots. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1-8. https://doi.org/10.1109/IROS.2017.8206429
  • Liu, Z., & Zhou, W. (2023). Energy-Efficient Algorithms for Path Coverage in Sensor Networks. Sensors, 23(11), 5026. https://doi.org/10.3390/s23115026
  • Mahajan, A., & Rock, S. (2020). Completeness Seeking Probabilistic Coverage Estimation using Uncertain State Estimates. IEEE Transactions on Robotics, 37(2), 427-442. https://doi.org/10.1109/TRO.2020.3043199
  • Nama, L. H., Huang, L., Li, X. J., & Xu, J. F. (2016). An Approach for Coverage Path Planning for UAVs. 2016 IEEE International Conference on Robotics and Automation (ICRA), 3208-3213. https://doi.org/10.1109/ICRA.2016.7496385
  • Özdemir, D. and Karaman, S. (2017). Investigating interactions between students with mild mental retardation and humanoid robot in terms of feedback types. Ted Eğitim ve Bilim. 42, 191, 109-138 https://doi.org/10.15390/eb.2017.6948
  • Pérez-González, A., Benítez-Montoya, N., Jaramillo-Duque, Á., & Cano-Quintero, J. B. (2021). Coverage Path Planning with Semantic Segmentation for UAV in PV Plants. International Journal of Advanced Computer Science and Applications, 12(11), 287-296. https://doi.org/10.14569/IJACSA.2021.0121136
  • Rodrigues, R. T., & Aguiar, A. P. (2018). A Coverage Planner for AUVs Using B-splines. OCEANS 2018 MTS/IEEE Charleston, 1-8. https://doi.org/10.1109/OCEANS.2018.8729760
  • Ranjitha, T. R., & Guruprasad, K. R. (2016). Pseudo Spanning Tree-based Complete and Competitive Robot Coverage Using Virtual Nodes. Procedia Computer Science, 89, 292-299. https://doi.org/10.1016/j.procs.2016.06.052
  • Šelek, A., Seder, M., Brezak, M., & Petrović, I. (2022). Smooth Complete Coverage Trajectory Planning Algorithm for a Nonholonomic Robot. Sensors, 22(23), 9269. https://doi.org/10.3390/s22239269
  • Thiayagarajan, K., & Balaji, C. G. (2012). Traversal Algorithm for Complete Coverage. Journal of Computer Science, 8(12), 2032-2041. https://doi.org/10.3844/jcssp.2012.2032.2041
  • Xing, B.; Wang, X.; Yang, L.; Liu, Z.; Wu, Q. (2023). An Algorithm of Complete Coverage Path Planning for Unmanned Surface Vehicle Based on Reinforcement Learning. Journal of Marine Science and Engineering, 11(3), 645. https://doi.org/10.3390/jmse11030645
  • Zeng, B., Tang, J., Lam, T. L., & Wen, J. (2023). TMSTC*: A Path Planning Algorithm for Minimizing Turns in Multi-Robot Coverage. IEEE Robotics and Automation Letters, 8(9), 4819-4826. https://doi.org/10.1109/LRA.2023.3290366

Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri ve Uygulama

Year 2025, Volume: 25 Issue: 2, 329 - 340

Eylül Özer , A. Burak İnner

Abstract

Endüstriyel temizlik robotları, geniş ve karmaşık ortamlarda, özellikle fabrikalar ve büyük perakende alanlarında kullanılmaktadır. Bu robotların, engellere çarpmadan veya çok yaklaşmadan etkili bir şekilde çalışması kritik öneme sahiptir. Boustrophedon kapsama alanı temelli tam kapsama yol planlama algoritması, robotların bir alanı eksiksiz ve düzenli bir şekilde taramasını sağladığı için endüstriyel uygulamalarda sıkça tercih edilmektedir. Bu çalışmada, Robot Operating System (ROS) platformunda özelleştirilmiş bir boustrophedon kapsama alanı temelli yol planlama algoritması sunulmaktadır. Önerilen algoritma, klasik boustrophedon algoritmasına kıyasla güvenlik marjı yerine parametrik şişirme yarıçapı kullanarak robotun hareket alanını optimize etmektedir. Bu yöntem, robotun engellere yaklaşmadan alanı daha verimli kapsamasını sağlamaktadır. Gerçekleştirilen testlerde, önerilen algoritma, klasik boustrophedon algoritmasına kıyasla %98,2 kapsama yüzdesine ulaşarak daha yüksek bir kapsama sağlarken, dönüş sayısını %61 oranında azaltmıştır. Seyahat süresi ve yol uzunluğu gibi performans metriklerinde de kayda değer iyileştirmeler gözlemlenmiştir. Testlerde hesaplama süresi 44 saniye, yol takip süresi ise 101 saniye olarak ölçülmüştür. Robotun toplamda kat ettiği mesafe 19,43 metre olup, dönüş miktarı ise 19,56 radyan olarak belirlenmiştir. Bu sonuçlar, önerilen algoritmanın hem engelli hem de engelsiz ortamlarda daha kısa sürede daha yüksek kapsama oranıyla çalışabileceğini göstermektedir. Algoritma, endüstriyel temizlik robotları için önemli bir gelişme sunmakta ve geniş çaplı uygulamalarda etkin bir çözüm olarak öne çıkmaktadır.

Keywords

kapsam yol planlama coverage path planner tam yol kapsamı

References

  • An, V., Qu, Z., Crosby, F., Roberts, R., & An, V. (2020). A Triangulation-Based Coverage Path Planning. IEEE Transactions on Automation Science and Engineering, 15(4), 1653-1662. https://doi.org/10.1109/TASE.2018.2799927
  • Bähnemann, R., Lawrance, N., Chung, J. J., Pantic, M., Siegwart, R., & Nieto, J. (2021). Revisiting Boustrophedon Coverage Path Planning as a Generalized Traveling Salesman Problem. In J. M. R. Sivalingam, J. A. Movellan, & S. Ozawa (Eds.), Field and Service Robotics (pp. 237-252). Springer. https://doi.org/10.1007/978-981-15-9460-1_20
  • Beşkirli, M. and Tefek, M. (2019). Parçacık sürü optimizasyon algoritması kullanılarak optimum robot yolu planlama. European Journal of Science and Technology, 201-213. https://doi.org/10.31590/ejosat.637832
  • Bobkov, D., Kiechle, M., Hilsenbeck, S., & Steinbach, E. (2017). Room Segmentation in 3D Point Clouds Using Anisotropic Potential Fields. 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 1-6. https://doi.org/10.1109/ICCIC.2017.8524392
  • Bormann, R., Jordan, F., Hampp, J., & Hagele, M. (2018). Indoor Coverage Path Planning: Survey, Implementation, Analysis. 2018 IEEE International Conference on Robotics and Automation (ICRA), 1718-1725. https://doi.org/10.1109/ICRA.2018.8460566
  • Cai, Z., Li, S., Gan, Y., Zhang, R., & Zhang, Q. (2022). Research on Complete Coverage Path Planning Algorithms Based on A* Algorithms. Expert Systems with Applications, 207, 117738. https://doi.org/10.1016/j.eswa.2022.117738
  • Carvalho, J. P., & Aguiar, A. P. (2023). A Reinforcement Learning Based Online Coverage Path Planning Algorithm. IEEE Transactions on Automation Science and Engineering, 20(3), 1459-1471. https://doi.org/10.1109/TASE.2023.3272003
  • Chen, X., Tucker, T. M., Kurfess, T. R., & Vuduc, R. (2019). Adaptive Deep Path: Efficient Coverage of a Known Environment Under Various Configurations. IEEE Robotics and Automation Letters, 5(2), 1816-1823. https://doi.org/10.1109/LRA.2020.2966891
  • Choi, Y.-H., Lee, T.-K., Baek, S.-H., & Oh, S.-Y. (2009). Online Complete Coverage Path Planning for Mobile Robots Based on Linked Spiral Paths Using Constrained Inverse Distance Transform. Journal of Intelligent & Robotic Systems, 56(4), 539-555. https://doi.org/10.1007/s10846-009-9310-2
  • Chowdhury, J. C., & Prabhakar, P. (2023). Optimal Multi-Robot Coverage Path Planning for Agricultural Fields using Motion Dynamics. IEEE Access, 11, 76679-76689. https://doi.org/10.1109/ACCESS.2023.3289267
  • Dakulović, M., Horvatić, S., & Petrović, I. (2011). Complete Coverage D* Algorithm for Path Planning of a Floor-Cleaning Mobile Robot. IFAC Proceedings Volumes, 44(1), 11939-11944. https://doi.org/10.3182/20110828-6-IT1002.03306
  • Dönmez, E. and Kocamaz, A. (2019). Çoklu hedeflerin çoklu robotlara paylaştırılması için bir yük dengeleme sistemi. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 8(2), 533-548. https://doi.org/10.17798/bitlisfen.467757
  • Esfahani, M. A., Wang, H., Wu, K., & Yuan, S. (2020). Unsupervised Scene Categorization, Path Segmentation. IEEE Transactions on Intelligent Transportation Systems, 22(12), 7601-7613. https://doi.org/10.1109/TITS.2020.3034683
  • Gajjar, S., Bhadani, J., Dutta, P., & Rastogi, N. (2017). Complete Coverage Path Planning Algorithm for Known 2D Environment. 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 1-5. https://doi.org/10.1109/ICCIC.2017.8524392
  • Gezer, A. (2024). Parçalı hücresel genetik algoritma ile insansız hava aracı performansına dayalı yol planlama. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi. 40 (1), 135 - 154 https://doi.org/10.17341/gazimmfd.1156817
  • Guo, S., Wang, T., Huang, Y., & You, D. (2022). Path planning algorithm for sweeping robot full traversal cleaning area. IEEE Access, 10, 119273-119283. https://doi.org/10.1109/ACCESS.2022.3221437
  • Kleiner, A., Baravalle, R., Kolling, A., Pilotti, P., & Munich, M. (2017). A Solution to Room-by-Room Coverage for Autonomous Cleaning Robots. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1-8. https://doi.org/10.1109/IROS.2017.8206429
  • Liu, Z., & Zhou, W. (2023). Energy-Efficient Algorithms for Path Coverage in Sensor Networks. Sensors, 23(11), 5026. https://doi.org/10.3390/s23115026
  • Mahajan, A., & Rock, S. (2020). Completeness Seeking Probabilistic Coverage Estimation using Uncertain State Estimates. IEEE Transactions on Robotics, 37(2), 427-442. https://doi.org/10.1109/TRO.2020.3043199
  • Nama, L. H., Huang, L., Li, X. J., & Xu, J. F. (2016). An Approach for Coverage Path Planning for UAVs. 2016 IEEE International Conference on Robotics and Automation (ICRA), 3208-3213. https://doi.org/10.1109/ICRA.2016.7496385
  • Özdemir, D. and Karaman, S. (2017). Investigating interactions between students with mild mental retardation and humanoid robot in terms of feedback types. Ted Eğitim ve Bilim. 42, 191, 109-138 https://doi.org/10.15390/eb.2017.6948
  • Pérez-González, A., Benítez-Montoya, N., Jaramillo-Duque, Á., & Cano-Quintero, J. B. (2021). Coverage Path Planning with Semantic Segmentation for UAV in PV Plants. International Journal of Advanced Computer Science and Applications, 12(11), 287-296. https://doi.org/10.14569/IJACSA.2021.0121136
  • Rodrigues, R. T., & Aguiar, A. P. (2018). A Coverage Planner for AUVs Using B-splines. OCEANS 2018 MTS/IEEE Charleston, 1-8. https://doi.org/10.1109/OCEANS.2018.8729760
  • Ranjitha, T. R., & Guruprasad, K. R. (2016). Pseudo Spanning Tree-based Complete and Competitive Robot Coverage Using Virtual Nodes. Procedia Computer Science, 89, 292-299. https://doi.org/10.1016/j.procs.2016.06.052
  • Šelek, A., Seder, M., Brezak, M., & Petrović, I. (2022). Smooth Complete Coverage Trajectory Planning Algorithm for a Nonholonomic Robot. Sensors, 22(23), 9269. https://doi.org/10.3390/s22239269
  • Thiayagarajan, K., & Balaji, C. G. (2012). Traversal Algorithm for Complete Coverage. Journal of Computer Science, 8(12), 2032-2041. https://doi.org/10.3844/jcssp.2012.2032.2041
  • Xing, B.; Wang, X.; Yang, L.; Liu, Z.; Wu, Q. (2023). An Algorithm of Complete Coverage Path Planning for Unmanned Surface Vehicle Based on Reinforcement Learning. Journal of Marine Science and Engineering, 11(3), 645. https://doi.org/10.3390/jmse11030645
  • Zeng, B., Tang, J., Lam, T. L., & Wen, J. (2023). TMSTC*: A Path Planning Algorithm for Minimizing Turns in Multi-Robot Coverage. IEEE Robotics and Automation Letters, 8(9), 4819-4826. https://doi.org/10.1109/LRA.2023.3290366
There are 28 citations in total.

Details

Primary Language Turkish
Subjects Computer Software, Control Engineering, Mechatronics and Robotics (Other)
Journal Section Articles
Authors

Eylül Özer 0000-0002-7468-5810

A. Burak İnner 0000-0003-0933-654X

Early Pub Date March 28, 2025
Publication Date
Submission Date June 4, 2024
Acceptance Date October 15, 2024
Published in Issue Year 2025 Volume: 25 Issue: 2

Cite

APA Özer, E., & İnner, A. B. (2025). Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri ve Uygulama. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 25(2), 329-340.
AMA Özer E, İnner AB. Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri ve Uygulama. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. March 2025;25(2):329-340.
Chicago Özer, Eylül, and A. Burak İnner. “Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri Ve Uygulama”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 25, no. 2 (March 2025): 329-40.
EndNote Özer E, İnner AB (March 1, 2025) Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri ve Uygulama. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 25 2 329–340.
IEEE E. Özer and A. B. İnner, “Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri ve Uygulama”, Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 25, no. 2, pp. 329–340, 2025.
ISNAD Özer, Eylül - İnner, A. Burak. “Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri Ve Uygulama”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 25/2 (March 2025), 329-340.
JAMA Özer E, İnner AB. Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri ve Uygulama. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2025;25:329–340.
MLA Özer, Eylül and A. Burak İnner. “Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri Ve Uygulama”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 25, no. 2, 2025, pp. 329-40.
Vancouver Özer E, İnner AB. Endüstriyel Temizlik Robotları İçin Geliştirilen Yeni Bir Boustrophedon Tabanlı Kapsama Algoritması: Performans İyileştirmeleri ve Uygulama. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2025;25(2):329-40.
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