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GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
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Updated: Sep 1, 2025

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Completion Time Minimization for UAV-UGV-Enabled Data Collection.

Zhijian Li1, Wendong Zhao1, Cuntao Liu1

  • 1School of Communication Engineering, Army Engineering University, Nanjing 210007, China.

Sensors (Basel, Switzerland)
|August 12, 2022
PubMed
Summary

This study introduces a cooperative Unmanned Ground Vehicle (UGV) and Unmanned Aerial Vehicle (UAV) system for efficient data collection. The proposed strategy significantly reduces data collection time by optimizing UGV and UAV trajectories.

Keywords:
data collectionpath planningunmanned aerial vehicle–unmanned ground vehicle

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Area of Science:

  • Robotics and Automation
  • Wireless Sensor Networks
  • Data Science

Background:

  • Unmanned Aerial Vehicle (UAV)-enabled data collection faces challenges like sensor node (SN) energy limitations and UAV altitude restrictions.
  • Existing systems may struggle with data loss or delays when SNs cannot directly communicate with the UAV.

Purpose of the Study:

  • To develop a cooperative Unmanned Ground Vehicle (UGV)-UAV data collection system to overcome limitations of UAV-only systems.
  • To minimize data collection time in a mobile data collection network with ground and aerial nodes.

Main Methods:

  • Proposed two cooperative strategies: collaboration without and with information interaction between the UGV and UAV.
  • Developed a collaborative strategy selection algorithm integrating multi-stage SN association and UAV-UGV path optimization.
  • Employed convex optimization and genetic algorithms for trajectory optimization.

Main Results:

  • The proposed collaborative scheme effectively minimizes data collection time.
  • Simulation results demonstrate a 36% reduction in mission completion time compared to benchmark schemes.

Conclusions:

  • Cooperative UGV-UAV systems offer a robust solution for challenging data collection scenarios.
  • The proposed optimization algorithm significantly enhances efficiency in mobile data collection networks.