2019/06/02 by Ayush Datta, Datta, Ayush, Rahul Tallamraju +3
Computer Science · Engineering · #FOS: Computer and information sciences #Multiagent Systems (cs.MA) #Robotic Path Planning Algorithms #Robotics (cs.RO) #Robotics and Sensor-Based Localization #UAV Applications and Optimization
paper · pdf · doi:10.48550/arxiv.1906.00401
openalex publication_date 2019/06/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we simulated a distributed, cooperative path planning\ntechnique for multiple drones (~200) to explore an unknown region (~10,000\nconnected units) in the presence of obstacles. The map of an unknown region is\ndynamically created based on the information obtained from sensors and other\ndrones. The unknown area is considered a connected region made up of hexagonal\nunit cells. These cells are grouped to form larger cells called sub-areas. We\nuse long range and short range communication. The short-range communication\nwithin drones in smaller proximity helps avoid re-exploration of cells already\nexplored by companion drones located in the same subarea. The long-range\ncommunication helps drones identify next subarea to be targeted based on\nweighted RNN (Reverse nearest neighbor). Simulation results show that weighted\nRNN in a hexagonal representation makes exploration more efficient, scalable\nand resilient to communication failures.\n