Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2021, Cilt: 13 Sayı: 1, 55 - 65, 18.01.2021
https://doi.org/10.29137/umagd.686123

Öz

Kaynakça

  • Abdi H., Black T. & Nahavandi S. (2011). An adjustable force field for multiple robot mission and path planning. In Proceedings of the 2011 IEEE International Conference on Systems, Man, and Cybernetics, Anchorage, USA, 1950–1955. doi:10.1109/ICSMC.2011.6083957
  • Adrian L. R. & Ribickis L. (2013). Fuzzy logic analysis of photovoltaic data for obstacle avoidance or mapping robot. Elektronika Ir Elektrotechnika, 19(1), 1392-1215. doi:10.5755/j01.eee.19.1.3243
  • Alotaibi E. T. S. & Al-Rawi H. (2016). Push and spin: a complete multi-robot path planning algorithm. In Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision, Phukhet, Thailand, 13-15. doi:10.1109/ICARCV.2016.7838836
  • Berglund T., Brodnik A., Jonsson H., Staffanson M. Soderkvist I. (2010). Planning smooth and obstacle-avoiding B-spline paths for autonomous mining vehicles. IEEE Transactions on Automation Science and Engineering,7(1), 167-172. doi:10.1109/TASE.2009.2015886
  • Ganeshmurthy M. S. &vSuresh.G. R. (2015). Path planning algorithm for autonomous mobile robot in dynamic environment, In Proceedings of the 3rd International Conference on Signal Processing, Communication and Networking, Chennai, India. doi:10.1109/ICSCN.2015.7219901
  • Gong H., Yin C., Zhang, F., Hou Z., Zhang R. (2017). Path planning algorithm for unmanned vehicles based on target-oriented rapidly-exploring random tree. In Proceedings of the 11th Asian Control Conference (ASCC), Gold Coast, Australia, 760-765. doi:10.1109/ASCC.2017.8287266
  • Graetz G. & Michaels G. (2018). Robots at work. Review of Economics and Statistics, 100(5), 753-768. doi:10.1162/rest_a_00754
  • Howard A. (2006). Multi-robot simultaneous localization and mapping using particle filters. International Journal of Robotics Research, 25(12), 1243–1256. doi:10.1177/0278364906072250
  • Hussein A., Adel M., Bakr M., Shehata O. M. & Khamis A. (2014). Multi-robot task allocation for search and rescue missions, Journal of Physics: Conference Series, 570: 1–10. doi:10.1088/1742-6596/570/5/052006
  • Kermorgant O. (2018). A magnetic climbing robot to perform autonomous welding in the shipbuilding industry. Robotics and Computer-Integrated Manufacturing, 53, 178-186. doi:10.1016/j.rcim.2018.04.008
  • Kim H., Kim D., Kim H., Shin J.U. & Myung H. (2016). An extended any-angle path planning algorithm for maintaining formation of multi-agent jellyfish elimination robot system. International Journal of Control, Automation, and Systems, 14(2), 598–607. doi:10.1007/s12555-014-0349-0.
  • Koch P., May S., Schmidpeter M., Kuhn M., Pfitzner C., Merkl C., Koch R., Fees M., Martin J., Ammon D. & Nuchter A. (2016). Multi-robot localization and mapping based on signed distance functions. Journal of Intelligent & Robotic Systems, 83, 409–428. doi:10.1007/s10846-016-0375-7
  • Macwan A., Vilela J., Nejat G.& Benhabib B. (2016). Multi-robot deployment for wilderness search and rescue. International Journal of Robotics and Automation, 31(1), 45-51. doi:10.2316/Journal.206.2016.1.206-4366
  • Madhu B., Sakkaravarthi R., Singh G. M.; Diya R. &. Jha D. K. (2017). Modeling, simulation and mechatronics design of a wireless automatic fire fighting surveillance robot. Defence Science Journal, 67(5), 572–580. doi:10.14429/dsj.67.10237
  • Marjovi A. & Marques L. (2011). Multi-robot olfactory search in structured environments. Robotics and Autonomous Systems, 59,11867–11881. doi:10.1016/j.robot.2011.07.010
  • Moradi B. (2019). Multi-objective mobile robot path planning problem through learnable evolution model. Journal of Experimental & Theoretical Artificial Intelligence, 31(2), 325-348. doi: 10.1080/0952813X.2018.1549107
  • Nagy I. (2014). From exploring to optimal path planning: considering error of navigation in multi-agent mobile robot domain. Acta Polytechnica Hungarica, 11(6), 39-55. doi:10.12700/aph.11.06.2014.06.3
  • Nazarahari M., Khanmirza E., Doostie S. (2019). Multi-objective multi-robot path planning in continuous environment using an enhanced genetic algorithm. Expert Systems with Applications, 115, 106-120. doi:10.1016/j.eswa.2018.08.008
  • Özarslan Yatak M., Göktaş B. & Duran F. (2018). Design and implementation of Android-based autonomous human tracking vehicle. International Journal of Informatics Technologies. 11(2), 157-162. doi:10.17671/gazibtd.340566
  • Prabuwono A. S., Burhanuddin M. A. & Said S. M. (2008). Autonomous contour tracking using staircase method for industrial robot. In Proceedings of the 10th International Conference on Control Automation Robotics and Vision, Hanoi, Vietnam, 2272–2276. doi:10.1109/ICARCV.2008.4795886
  • Saeedi S., Paull L., Trentini M & Li H. (2011). Neural network-based multiple robot simultaneous localization and mapping. IEEE Transactions on Neural Networks, 22(12), 2376–2387. doi:10.1109/TNN.2011.2176541
  • Saeedi S., Paull L., Trentini M, & Li H. (2015). Occupancy grid map merging for multiple robot simultaneous localization and mapping. International Journal of Robotics and Automation, 149-157. doi:10.2316/Journal.206.2015.2.206-4028
  • Seçkin A.Ç., Özek A. & Karpuz C. Çoklu robotlarda işbirlikli davranışların karşılaştırılması ve bulanık mantık yaklaşımı. Politeknik, Erken Görünüm. doi:10.2339/politeknik.481177
  • Sun D., Kleiner A. & Wendt T.M. (2008). Multi-robot range-only SLAM by active sensor nodes for urban search and rescue. In Proceedings of the 12th annual RoboCup International Symposium, Suzhou, China 318–330. doi:10.1007/978-3-642-02921-9_28
  • Thabit S., Mohades A. (2019). Multi-robot path planning based on multi-objective particle swarm optimization. IEEE Access,7, 2138-2147. doi:10.1109/ACCESS.2018.2886245
  • Thor J., Schultz U. P. & Kuhrmann M. (2015). On the use of safety certification practices in autonomous field robot software development: A systematic mapping study. In Proceedings of the 16th International Conference on Product-Focused Software Process Improvement, Bolzano, Italy, 335–352. doi:10.1007/978-3-319-26844-6_25
  • Tominaga A.; Hayashi E. & Sasao T. (2017). Localization method of autonomous moving robot for forest industry. In Proceedings of the International Conference on Artificial Life and Robotics, Miyazaki, 376-379.

Implementation of Collaborative Multi-Robot System Carrying Cargos Autonomously

Yıl 2021, Cilt: 13 Sayı: 1, 55 - 65, 18.01.2021
https://doi.org/10.29137/umagd.686123

Öz

The paper presents implementation of collaborative multi-robot system for carrying cargo autonomously. Multi-robot systems are especially used to carry cargos to target place in the shortest way in the shortest duration by path planning. This system is composed of two robots called as Leader and Assistant. They sense the cargo with load cells on themselves and carry it to the target place. After determination of the cargo, if its weight is in the limits of the weights for Leader, it pushes the cargo by itself and Assistant waits on standby mode. If the cargo is higher than carrying capacity of Leader, Assistant is called and both push it to the target. Detecting cargos task is performed with a method similar to method of calculating fitness value. Carrying cargos task was performed by finding the shortest way with curve fitting algorithm. Carrying cargos with multi-robots by using curve fitting is the most practical solution. Consequently, reducing the route by 13.7% could be provided successfully by this algorithm instead of line following method and so energy saving was ensured. Task performance rate for carrying the cargo to the target place is achieved up to 90% for stand-alone and cooperative operation.

Kaynakça

  • Abdi H., Black T. & Nahavandi S. (2011). An adjustable force field for multiple robot mission and path planning. In Proceedings of the 2011 IEEE International Conference on Systems, Man, and Cybernetics, Anchorage, USA, 1950–1955. doi:10.1109/ICSMC.2011.6083957
  • Adrian L. R. & Ribickis L. (2013). Fuzzy logic analysis of photovoltaic data for obstacle avoidance or mapping robot. Elektronika Ir Elektrotechnika, 19(1), 1392-1215. doi:10.5755/j01.eee.19.1.3243
  • Alotaibi E. T. S. & Al-Rawi H. (2016). Push and spin: a complete multi-robot path planning algorithm. In Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision, Phukhet, Thailand, 13-15. doi:10.1109/ICARCV.2016.7838836
  • Berglund T., Brodnik A., Jonsson H., Staffanson M. Soderkvist I. (2010). Planning smooth and obstacle-avoiding B-spline paths for autonomous mining vehicles. IEEE Transactions on Automation Science and Engineering,7(1), 167-172. doi:10.1109/TASE.2009.2015886
  • Ganeshmurthy M. S. &vSuresh.G. R. (2015). Path planning algorithm for autonomous mobile robot in dynamic environment, In Proceedings of the 3rd International Conference on Signal Processing, Communication and Networking, Chennai, India. doi:10.1109/ICSCN.2015.7219901
  • Gong H., Yin C., Zhang, F., Hou Z., Zhang R. (2017). Path planning algorithm for unmanned vehicles based on target-oriented rapidly-exploring random tree. In Proceedings of the 11th Asian Control Conference (ASCC), Gold Coast, Australia, 760-765. doi:10.1109/ASCC.2017.8287266
  • Graetz G. & Michaels G. (2018). Robots at work. Review of Economics and Statistics, 100(5), 753-768. doi:10.1162/rest_a_00754
  • Howard A. (2006). Multi-robot simultaneous localization and mapping using particle filters. International Journal of Robotics Research, 25(12), 1243–1256. doi:10.1177/0278364906072250
  • Hussein A., Adel M., Bakr M., Shehata O. M. & Khamis A. (2014). Multi-robot task allocation for search and rescue missions, Journal of Physics: Conference Series, 570: 1–10. doi:10.1088/1742-6596/570/5/052006
  • Kermorgant O. (2018). A magnetic climbing robot to perform autonomous welding in the shipbuilding industry. Robotics and Computer-Integrated Manufacturing, 53, 178-186. doi:10.1016/j.rcim.2018.04.008
  • Kim H., Kim D., Kim H., Shin J.U. & Myung H. (2016). An extended any-angle path planning algorithm for maintaining formation of multi-agent jellyfish elimination robot system. International Journal of Control, Automation, and Systems, 14(2), 598–607. doi:10.1007/s12555-014-0349-0.
  • Koch P., May S., Schmidpeter M., Kuhn M., Pfitzner C., Merkl C., Koch R., Fees M., Martin J., Ammon D. & Nuchter A. (2016). Multi-robot localization and mapping based on signed distance functions. Journal of Intelligent & Robotic Systems, 83, 409–428. doi:10.1007/s10846-016-0375-7
  • Macwan A., Vilela J., Nejat G.& Benhabib B. (2016). Multi-robot deployment for wilderness search and rescue. International Journal of Robotics and Automation, 31(1), 45-51. doi:10.2316/Journal.206.2016.1.206-4366
  • Madhu B., Sakkaravarthi R., Singh G. M.; Diya R. &. Jha D. K. (2017). Modeling, simulation and mechatronics design of a wireless automatic fire fighting surveillance robot. Defence Science Journal, 67(5), 572–580. doi:10.14429/dsj.67.10237
  • Marjovi A. & Marques L. (2011). Multi-robot olfactory search in structured environments. Robotics and Autonomous Systems, 59,11867–11881. doi:10.1016/j.robot.2011.07.010
  • Moradi B. (2019). Multi-objective mobile robot path planning problem through learnable evolution model. Journal of Experimental & Theoretical Artificial Intelligence, 31(2), 325-348. doi: 10.1080/0952813X.2018.1549107
  • Nagy I. (2014). From exploring to optimal path planning: considering error of navigation in multi-agent mobile robot domain. Acta Polytechnica Hungarica, 11(6), 39-55. doi:10.12700/aph.11.06.2014.06.3
  • Nazarahari M., Khanmirza E., Doostie S. (2019). Multi-objective multi-robot path planning in continuous environment using an enhanced genetic algorithm. Expert Systems with Applications, 115, 106-120. doi:10.1016/j.eswa.2018.08.008
  • Özarslan Yatak M., Göktaş B. & Duran F. (2018). Design and implementation of Android-based autonomous human tracking vehicle. International Journal of Informatics Technologies. 11(2), 157-162. doi:10.17671/gazibtd.340566
  • Prabuwono A. S., Burhanuddin M. A. & Said S. M. (2008). Autonomous contour tracking using staircase method for industrial robot. In Proceedings of the 10th International Conference on Control Automation Robotics and Vision, Hanoi, Vietnam, 2272–2276. doi:10.1109/ICARCV.2008.4795886
  • Saeedi S., Paull L., Trentini M & Li H. (2011). Neural network-based multiple robot simultaneous localization and mapping. IEEE Transactions on Neural Networks, 22(12), 2376–2387. doi:10.1109/TNN.2011.2176541
  • Saeedi S., Paull L., Trentini M, & Li H. (2015). Occupancy grid map merging for multiple robot simultaneous localization and mapping. International Journal of Robotics and Automation, 149-157. doi:10.2316/Journal.206.2015.2.206-4028
  • Seçkin A.Ç., Özek A. & Karpuz C. Çoklu robotlarda işbirlikli davranışların karşılaştırılması ve bulanık mantık yaklaşımı. Politeknik, Erken Görünüm. doi:10.2339/politeknik.481177
  • Sun D., Kleiner A. & Wendt T.M. (2008). Multi-robot range-only SLAM by active sensor nodes for urban search and rescue. In Proceedings of the 12th annual RoboCup International Symposium, Suzhou, China 318–330. doi:10.1007/978-3-642-02921-9_28
  • Thabit S., Mohades A. (2019). Multi-robot path planning based on multi-objective particle swarm optimization. IEEE Access,7, 2138-2147. doi:10.1109/ACCESS.2018.2886245
  • Thor J., Schultz U. P. & Kuhrmann M. (2015). On the use of safety certification practices in autonomous field robot software development: A systematic mapping study. In Proceedings of the 16th International Conference on Product-Focused Software Process Improvement, Bolzano, Italy, 335–352. doi:10.1007/978-3-319-26844-6_25
  • Tominaga A.; Hayashi E. & Sasao T. (2017). Localization method of autonomous moving robot for forest industry. In Proceedings of the International Conference on Artificial Life and Robotics, Miyazaki, 376-379.
Toplam 27 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Emrah Budak Bu kişi benim 0000-0002-5442-7697

Fecir Duran 0000-0001-7256-5471

Meral Özarslan Yatak 0000-0002-1091-1647

Raif Bayır 0000-0003-3155-8771

Yayımlanma Tarihi 18 Ocak 2021
Gönderilme Tarihi 7 Şubat 2020
Yayımlandığı Sayı Yıl 2021 Cilt: 13 Sayı: 1

Kaynak Göster

APA Budak, E., Duran, F., Özarslan Yatak, M., Bayır, R. (2021). Implementation of Collaborative Multi-Robot System Carrying Cargos Autonomously. International Journal of Engineering Research and Development, 13(1), 55-65. https://doi.org/10.29137/umagd.686123
Tüm hakları saklıdır. Kırıkkale Üniversitesi, Mühendislik Fakültesi.