تقرير
M-SET: Multi-Drone Swarm Intelligence Experimentation with Collision Avoidance Realism
| العنوان: | M-SET: Multi-Drone Swarm Intelligence Experimentation with Collision Avoidance Realism |
|---|---|
| المؤلفون: | Qin, Chuhao, Robins, Alexander, Lillywhite-Roake, Callum, Pearce, Adam, Mehta, Hritik, James, Scott, Wong, Tsz Ho, Pournaras, Evangelos |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Robotics, Computer Science - Distributed, Parallel, and Cluster Computing |
| الوصف: | Distributed sensing by cooperative drone swarms is crucial for several Smart City applications, such as traffic monitoring and disaster response. Using an indoor lab with inexpensive drones, a testbed supports complex and ambitious studies on these systems while maintaining low cost, rigor, and external validity. This paper introduces the Multi-drone Sensing Experimentation Testbed (M-SET), a novel platform designed to prototype, develop, test, and evaluate distributed sensing with swarm intelligence. M-SET addresses the limitations of existing testbeds that fail to emulate collisions, thus lacking realism in outdoor environments. By integrating a collision avoidance method based on a potential field algorithm, M-SET ensures collision-free navigation and sensing, further optimized via a multi-agent collective learning algorithm. Extensive evaluation demonstrates accurate energy consumption estimation and a low risk of collisions, providing a robust proof-of-concept. New insights show that M-SET has significant potential to support ambitious research with minimal cost, simplicity, and high sensing quality. Comment: 7 pages, 7 figures. This work has been submitted to the IEEE conferenece |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2406.10916 |
| رقم الأكسشن: | edsarx.2406.10916 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |