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This paper presents a communication and energy-aware multi-UAV Coverage Path Planning (mCPP) method for scenarios requiring continuous inter-UAV communication, such as cooperative search and rescue and surveillance missions. Unlike existing…

Robotics · Computer Science 2025-04-22 Mohamed Samshad , Ketan Rajawat

Coverage path planning (CPP) is the task of designing a trajectory that enables a mobile agent to travel over every point of an area of interest. We propose a new method to control an unmanned aerial vehicle (UAV) carrying a camera on a CPP…

Robotics · Computer Science 2021-02-15 Mirco Theile , Harald Bayerlein , Richard Nai , David Gesbert , Marco Caccamo

This paper tackles the problem of planning minimum-energy coverage paths for multiple UAVs. The addressed Multi-UAV Coverage Path Planning (mCPP) is a crucial problem for many UAV applications such as inspection and aerial survey. However,…

Robotics · Computer Science 2024-02-19 Denys Datsko , Frantisek Nekovar , Robert Penicka , Martin Saska

Unmanned Aerial Vehicle (UAV) Coverage Path Planning (CPP) is critical for applications such as precision agriculture and search and rescue. While traditional methods rely on discrete grid-based representations, real-world UAV operations…

Coverage path planning (CPP) is a critical problem in robotics, where the goal is to find an efficient path that covers every point in an area of interest. This work addresses the power-constrained CPP problem with recharge for…

Robotics · Computer Science 2024-10-28 Mirco Theile , Harald Bayerlein , Marco Caccamo , Alberto L. Sangiovanni-Vincentelli

This paper proposes a novel mission planning platform, capable of efficiently deploying a team of UAVs to cover complex-shaped areas, in various remote sensing applications. Under the hood lies a novel optimization scheme for grid-based…

This article addresses the problem of Cooperative Coverage Path Planning (C-CPP) for the inspection of complex infrastructures (offline 3D reconstruction) by utilizing multiple Unmanned Autonomous Vehicles (UAVs). The proposed scheme, based…

Modern coverage path planning (CPP) for holonomic UAVs in emergency response must contend with diverse environments where regions of interest (ROIs) often take the form of highly irregular polygons, characterized by asymmetric shapes, dense…

Robotics · Computer Science 2025-09-25 Pedro Antonio Alarcon Granadeno , Jane Cleland-Huang

We present a multi-UAV Coverage Path Planning (CPP) framework for the inspection of large-scale, complex 3D structures. In the proposed sampling-based coverage path planning method, we formulate the multi-UAV inspection applications as a…

Robotics · Computer Science 2020-07-28 Wei Jing , Di Deng , Yan Wu , Kenji Shimada

Unmanned aerial vehicles (UAVs) are increasingly utilized in global search and rescue efforts, enhancing operational efficiency. In these missions, a coordinated swarm of UAVs is deployed to efficiently cover expansive areas by capturing…

Robotics · Computer Science 2024-05-21 Sina Kazemdehbashi , Yanchao Liu

Coverage path planning with unmanned aerial vehicles (UAVs) is a core task for many services and applications including search and rescue, precision agriculture, infrastructure inspection and surveillance. This work proposes an integrated…

Systems and Control · Electrical Eng. & Systems 2023-05-23 Savvas Papaioannou , Panayiotis Kolios , Theocharis Theocharides , Christos G. Panayiotou , Marios M. Polycarpou

This paper presents a novel multi-robot coverage path planning (CPP) algorithm - aka SCoPP - that provides a time-efficient solution, with workload balanced plans for each robot in a multi-robot system, based on their initial states. This…

Coverage Path Planning (CPP) is vital in precision agriculture to improve efficiency and resource utilization. In irregular and dispersed plantations, traditional grid-based CPP often causes redundant coverage over non-vegetated areas,…

Robotics · Computer Science 2025-05-09 Weijie Kuang , Hann Woei Ho , Ye Zhou

Most consumer-level low-cost unmanned aerial vehicles (UAVs) have limited battery power and long charging time. Due to these energy constraints, they cannot accomplish many practical tasks, such as monitoring a sport or political event for…

Robotics · Computer Science 2021-01-27 Jyh-Ming Lien , Sam Rodriguez , Marco Morales

Planning the path to gather the surface information of the target objects is crucial to improve the efficiency of and reduce the overall cost, for visual inspection applications with Unmanned Aerial Vehicles (UAVs). Coverage Path Planning…

Robotics · Computer Science 2019-08-09 Wei Jing , Di Deng , Zhe Xiao , Yong Liu , Kenji Shimada

This letter addresses the 3D coverage path planning (CPP) problem for terrain reconstruction of unknown obstacle rich environments. Due to sensing limitations, the proposed method, called CT-CPP, performs layered scanning of the 3D region…

Robotics · Computer Science 2021-12-03 Zongyuan Shen , Junnan Song , Khushboo Mittal , Shalabh Gupta

This paper addresses the Dynamic UGV-UAV Cooperative Path Planning (DUCPP) problem involving one unmanned ground vehicle (UGV) assisted by one or more unmanned aerial vehicles (UAVs) operating on an uncertain road network with potentially…

Robotics · Computer Science 2026-04-29 Ninh Nguyen , Srinivas Akella

Unmanned Aerial Vehicles (UAVs), although adept at aerial surveillance, are often constrained by limited battery capacity. By refueling on slow-moving Unmanned Ground Vehicles (UGVs), their operational endurance can be significantly…

Low cost Unmanned Aerial Vehicles (UAVs) need multiple refuels to accomplish large area coverage. The number of refueling stations and their placement plays a vital role in determining coverage efficiency. In this paper, we propose the use…

Robotics · Computer Science 2018-05-14 Parikshit Maini , Kaarthik Sundar , Sivakumar Rathinam , PB Sujit

Coverage path planning (CPP) is the problem of finding a path that covers the entire free space of a confined area, with applications ranging from robotic lawn mowing to search-and-rescue. When the environment is unknown, the path needs to…

Robotics · Computer Science 2024-06-10 Arvi Jonnarth , Jie Zhao , Michael Felsberg
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