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Area of Science:

  • Planetary Science
  • Robotics
  • Geoscience

Background:

  • Robotic planetary exploration requires specialized datasets for method development.
  • Existing datasets may not fully represent the complexities of extraterrestrial environments.

Purpose of the Study:

  • To present a novel dataset for advancing robotic perception, localization, and navigation.
  • To support the evaluation and validation of Guidance, Navigation, and Control (GNC) systems.

Main Methods:

  • Acquired rover sensor data (optical, thermal, inertial, force-torque) during 1.7km traverses in Bardenas semi-desert.
  • Generated a high-resolution 3D map of the test terrain.
  • Collected laser-induced breakdown spectroscopy (LIBS) data of rock samples and local weather data.

Main Results:

  • A comprehensive dataset combining scientific and engineering instrument data was obtained.
  • The dataset includes unique sensor data from thermal cameras and force-torque sensors.
  • The data facilitates research on GNC in unstructured planetary-analog environments.

Conclusions:

  • This dataset provides a valuable resource for the advancement of autonomous robotic exploration.
  • The inclusion of diverse sensor data enables in-depth analysis of rover performance.
  • It serves as a benchmark for testing novel algorithms in realistic Martian-analog conditions.