ROS-Based Approach for Optimizing Multi-Drone Navigation in Dynamic Environments with Seamless Integration Sim-to-Real Transition

multi-drone systems are increasingly being applied to perform surveillance, delivery, and infrastructure inspection tasks. Navigation in dynamic environments remains one of the most critical challenges with multi-drones, so robust solutions are urgently required to enable real-time adaptation. This paper presents a (Robot Operating System) ROS-driven approach for optimizing multi-drone navigation. Simulation environments will provide useful ground for initial development and testing with smooth transitions to practical applications. These include, among others, dynamic obstacle avoidance algorithms, strategies for cooperative path planning, and the related communication protocols to be used in synchronized operations. The proof of effectiveness through extensive simulations and experiments shows scalability in complex and dynamic situations. For this fast-evolving domain of autonomous robotics, multiple drones in dynamically changing environments are given several open challenges and opportunities. The paper proposes a new approach to optimization for multi-drone navigation based on ROS. This approach focuses on a smooth transition from simulation to the real world by addressing two imperative concerns coordination and collision avoidance within dynamic conditions. In this context, we will present the implementation of advanced algorithms for obstacle detection and path planning within a robust ROS framework to ensure efficient and safe navigation. Extensive simulation experiments were conducted to confirm the efficiency of our method, representing major improvements in navigation performance. Besides, real-world tests confirm in practice the reliability and adaptability of the system for search and rescue, surveillance, and environmental monitoring. This represents another important brick in the growing knowledge about autonomous drone systems, and it will provide useful hints for practical applications that will take place shortly.

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Published
2025-06-20
DOI
https://doi.org/10.1109/conit65521.2025.11166806
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

ROS-Based Approach for Optimizing Multi-Drone Navigation in Dynamic Environments with Seamless Integration Sim-to-Real Transition

Lade. Gunakar Rao, Erupaka Nitya, A. O. Busari, Thallapally Sravani et al.
Robotic Path Planning Algorithms
article

ROS-Based Approach for Optimizing Multi-Drone Navigation in Dynamic Environments with Seamless Integration Sim-to-Real Transition

Lade. Gunakar Rao, Erupaka Nitya, A. O. Busari, Thallapally Sravani, Shireesha Thikka
article en

Abstract

multi-drone systems are increasingly being applied to perform surveillance, delivery, and infrastructure inspection tasks. Navigation in dynamic environments remains one of the most critical challenges with multi-drones, so robust solutions are urgently required to enable real-time adaptation. This paper presents a (Robot Operating System) ROS-driven approach for optimizing multi-drone navigation. Simulation environments will provide useful ground for initial development and testing with smooth transitions to practical applications. These include, among others, dynamic obstacle avoidance algorithms, strategies for cooperative path planning, and the related communication protocols to be used in synchronized operations. The proof of effectiveness through extensive simulations and experiments shows scalability in complex and dynamic situations. For this fast-evolving domain of autonomous robotics, multiple drones in dynamically changing environments are given several open challenges and opportunities. The paper proposes a new approach to optimization for multi-drone navigation based on ROS. This approach focuses on a smooth transition from simulation to the real world by addressing two imperative concerns coordination and collision avoidance within dynamic conditions. In this context, we will present the implementation of advanced algorithms for obstacle detection and path planning within a robust ROS framework to ensure efficient and safe navigation. Extensive simulation experiments were conducted to confirm the efficiency of our method, representing major improvements in navigation performance. Besides, real-world tests confirm in practice the reliability and adaptability of the system for search and rescue, surveillance, and environmental monitoring. This represents another important brick in the growing knowledge about autonomous drone systems, and it will provide useful hints for practical applications that will take place shortly.

National Institute of Technology Warangal (IN), Social Welfare Department (HK), Swami Vivekanand College of Pharmacy (IN)
Openalex Percentile: Top 74%
Robotic Path Planning Algorithms
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