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Swarm robotics is a research field inspired from the natural behavior of ants, bees or fish in their natural habitat. Each group display swarm behavior in different ways. For example, ants use pheromones to trace one another in order to find a nest, reach a food source or do any operation,...
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| Format: | Thesis |
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AUC Knowledge Fountain
2018
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| _version_ | 1867613410288467968 |
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| access_status_str | Open Access |
| author | Hamouda, Aalaa Ibrahim |
| author_browse | Hamouda, Aalaa Ibrahim |
| author_facet | Hamouda, Aalaa Ibrahim |
| author_sort | Hamouda, Aalaa Ibrahim |
| collection | Thesis |
| dc_rights_str_mv | The author retains all rights with regard to copyright. The author certifies that written permission from the owner(s) of third-party copyrighted matter included in the thesis, dissertation, paper, or record of study has been obtained. The author further certifies that IRB approval has been obtained for this thesis, or that IRB approval is not necessary for this thesis. Insofar as this thesis, dissertation, paper, or record of study is an educational record as defined in the Family Educational Rights and Privacy Act (FERPA) (20 USC 1232g), the author has granted consent to disclosure of it to anyone who requests a copy. |
| description | Swarm robotics is a research field inspired from the natural behavior of ants, bees or fish in their natural habitat. Each group display swarm behavior in different ways. For example, ants use pheromones to trace one another in order to find a nest, reach a food source or do any operation, while bees use dance moves to attract one another to the desired place. In swarm robotics, small robots attempt to mimic insect behavior. The robotic swarm group collaborate to perform a task and collectively solve a given problem. In the process, the robots use the sensors they are equipped with to move, communicate or avoid obstacles until they collectively do the desired functionality. In this thesis, we propose a modification to the Robotic Darwinian Particle Swarm Optimization (RDPSO) algorithm. In the RDPSO, robots deployed in a rescue operation, transport one object at a time to a desired safe place. In our algorithm, we simultaneously transport multiple objects to safety. We call our algorithm Multi Robotics Darwinian Particle Swarm Optimization (MRDPSO). Our algorithm is developed and implemented on a VREP simulator using ePuck robots as swarm members. We test our algorithm using two different environment sizes complete with obstacles. First implementation is for two simultaneous object transported but can be extended to more than two. We compare our new algorithm to the results of single RDPSO and found our algorithm to be 35 to 41 % faster. We also compared our results to those obtained from three selected papers that are Ghosh, Konar, and Janarthanan [1], TORABI [2], and Kube and Bonabeau [3]. The performance measures we compare to are the accuracy of transporting all objects to desired location, and the time efficiency of transporting all the objects in our new system. |
| format | Thesis |
| id | oai:fount.aucegypt.edu:etds-1459 |
| institution | American University in Cairo (Egypt) |
| last_indexed | 2026-06-10T12:35:42.290Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from AUC Knowledge Fountain — bepress |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | AUC Knowledge Fountain |
| publisherStr | AUC Knowledge Fountain |
| record_format | dspace |
| source_str | AUC Knowledge Fountain — bepress |
| spelling | oai:fount.aucegypt.edu:etds-1459 Cooperative transport in swarm robotics. Multi object transportation Hamouda, Aalaa Ibrahim Swarm robotics is a research field inspired from the natural behavior of ants, bees or fish in their natural habitat. Each group display swarm behavior in different ways. For example, ants use pheromones to trace one another in order to find a nest, reach a food source or do any operation, while bees use dance moves to attract one another to the desired place. In swarm robotics, small robots attempt to mimic insect behavior. The robotic swarm group collaborate to perform a task and collectively solve a given problem. In the process, the robots use the sensors they are equipped with to move, communicate or avoid obstacles until they collectively do the desired functionality. In this thesis, we propose a modification to the Robotic Darwinian Particle Swarm Optimization (RDPSO) algorithm. In the RDPSO, robots deployed in a rescue operation, transport one object at a time to a desired safe place. In our algorithm, we simultaneously transport multiple objects to safety. We call our algorithm Multi Robotics Darwinian Particle Swarm Optimization (MRDPSO). Our algorithm is developed and implemented on a VREP simulator using ePuck robots as swarm members. We test our algorithm using two different environment sizes complete with obstacles. First implementation is for two simultaneous object transported but can be extended to more than two. We compare our new algorithm to the results of single RDPSO and found our algorithm to be 35 to 41 % faster. We also compared our results to those obtained from three selected papers that are Ghosh, Konar, and Janarthanan [1], TORABI [2], and Kube and Bonabeau [3]. The performance measures we compare to are the accuracy of transporting all objects to desired location, and the time efficiency of transporting all the objects in our new system. 2018-06-01T07:00:00Z thesis application/pdf https://fount.aucegypt.edu/etds/460 https://fount.aucegypt.edu/context/etds/article/1459/viewcontent/Aalaa_20Hamouda_Thesis.pdf The author retains all rights with regard to copyright. The author certifies that written permission from the owner(s) of third-party copyrighted matter included in the thesis, dissertation, paper, or record of study has been obtained. The author further certifies that IRB approval has been obtained for this thesis, or that IRB approval is not necessary for this thesis. Insofar as this thesis, dissertation, paper, or record of study is an educational record as defined in the Family Educational Rights and Privacy Act (FERPA) (20 USC 1232g), the author has granted consent to disclosure of it to anyone who requests a copy. Theses and Dissertations AUC Knowledge Fountain Cooperative transport Swarm robotics |
| spellingShingle | Cooperative transport Swarm robotics Hamouda, Aalaa Ibrahim Cooperative transport in swarm robotics. Multi object transportation |
| title | Cooperative transport in swarm robotics. Multi object transportation |
| title_full | Cooperative transport in swarm robotics. Multi object transportation |
| title_fullStr | Cooperative transport in swarm robotics. Multi object transportation |
| title_full_unstemmed | Cooperative transport in swarm robotics. Multi object transportation |
| title_short | Cooperative transport in swarm robotics. Multi object transportation |
| title_sort | cooperative transport in swarm robotics multi object transportation |
| topic | Cooperative transport Swarm robotics |
| url | https://fount.aucegypt.edu/etds/460 https://fount.aucegypt.edu/context/etds/article/1459/viewcontent/Aalaa_20Hamouda_Thesis.pdf |
| work_keys_str_mv | AT hamoudaaalaaibrahim cooperativetransportinswarmroboticsmultiobjecttransportation |