Exact(8)
Current 3D terrain field coverage path planning algorithms are simply 2D coverage path planning projected into 3D through field terrain represented by the field's Digital Elevation Model (DEM).
Also, a novel side-to-side 3D coverage path planning approach, which ensures zero skips/overlaps regardless of the topographical nature of the field terrain, is developed.
This paper contributes to the field of multi-agent coverage path planning for structural inspection and provides experimental validation of the control and inspection results.
With thousands of existing ROS packages, distributed or swarm robotic experiment settings (e.g., multi-robot coverage path planning [9]) can be quickly constructed.
The coverage path planning (CPP) problem belongs to a sub-field of motion planning where the goal is to compute a complete coverage trajectory from initial to final position, within the robot workspace subjected to a set of restrictions.
Multi-robot sensor-based coverage path planning requires every point given in the workspace has to be covered at least by a sensor of a robot in the robot team.
Similar(52)
Evaluation results show that the proposed coverage and path planning scheme results in better coverage and energy consumption than traditional coverage and path planning techniques for UAVs.
A new mathematical model for positioning alternative fuel (AF) refueling stations on directed-transportation networks with the objective of maximizing the coverage of path flow volume is proposed.
This paper proposes a new quality-aware and energy-efficient UAV coverage and path planning scheme with the objective of sensing a geometrically complex target area with satisfactory spatial and temporal resolutions.
Another feature of the path coverage that we like to study is the quality of the coverage in terms of the size of the gaps on.
Path coverage by a random network (or barrier coverage which is a relaxed version of the path coverage) has been the focus of some previous work [1 6].
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