A survey on coverage path planning for robotics

By Enric Galceran, M. Carreras. Robotics Auton. Syst., 2013

1,583 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/a9c7f3a32865088a1113ba415178cbd14db2b663

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Silvio Savarese
2. Alexander Toshev
3. Li Fei-Fei
4. Lisane Brisolara de Brisolara
5. Paulo R. Ferreira Jr.
6. Tauã Milech Cabreira
7. Guilherme A. S. Pereira
8. Kuan Fang

In Computer Vision and Pattern Recognition

1. Li Fei-Fei
2. Silvio Savarese
3. Luc Van Gool
4. Jitendra Malik
5. Kristen Grauman
6. Trevor Darrell
7. Xiaogang Wang
8. Andrew Zisserman

In Control and Systems Engineering

1. Silvio Savarese
2. Li Fei-Fei
3. Alexander Toshev
4. R. Mohd-Mokhtar
5. Kuan Fang
6. Lisane Brisolara de Brisolara
7. Paulo R. Ferreira Jr.
8. Chee Sheng Tan

Citations in the corpus

• Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks (2019, background): “The coverage and search tasks are studied in robotics, however, primarily in explored environments and are concerned about optimal path planning [12].”
• Survey of Robot 3D Path Planning Algorithms (2016, background): “Surveys such as [13] almost all analyze the path planning problems under 2D condition.”
• A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms (2021, background): “In the past decade, Galceran and Carreras [18] have reviewed CPP for robotics literature.”
• Survey on Coverage Path Planning with Unmanned Aerial Vehicles (2019, methodology): “Grid-based methods can be applied over approximate areas to generate coverage paths [21].”
• Energy-Aware Coverage Path Planning of UAVs (2015, background): “Most of the work on CPP, however, has taken only geometrical constraints into account without consideringthe peculiar features of the UAV, (e.g., the available energy, the weight, the maximum speed) and other mission requirements, (e.g., the spacial resolution of the acquired images).”
• Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey (2018, background): “Coverage path planning with drones refers to finding paths of drones such that all points of some area P are covered at least once (see general surveys by Choset [49] and Galceran and Carreras [87] on coverage path planning for robotics).”
• Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time (2015, background): “A comprehensive recent survey of methods can be found in [5].”