Robotic Localization and Multi-Sensor, Semantic 3D Mapping for Exploration of Subsurface Voids
Abstract
Robotic exploration of subsurface voids (SSV) has seen rapid advancements in recent years. These advances bring compelling technologies into consideration for the exploration of SSV on other worlds. A critical component of these technologies is 3D Simultaneous Localization And Mapping (SLAM), which provides capabilities for a robot to both know where it is and generate a 3D map of the environment around it. These capabilities are also critical for scientific exploration. Location estimates provide a global context to measurements, identifying how far underground, and how far from the entrance a robot is, to help inform which phase of the cave system it is in. Accurate measurements of a robot's location are also essential for enabling robotic navigation and obstacle avoidance. SLAM also produces a 3D map of the environment, giving valuable insights into the cave geometry as a product in and of itself, as well as providing context for other measurements with reference to the cave geometry.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMP057...03M
- Keywords:
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- 0406 Astrobiology and extraterrestrial materials;
- BIOGEOSCIENCES;
- 6225 Mars;
- PLANETARY SCIENCES: SOLAR SYSTEM OBJECTS;
- 6297 Instruments and techniques;
- PLANETARY SCIENCES: SOLAR SYSTEM OBJECTS;
- 5430 Interiors;
- PLANETARY SCIENCES: SOLID SURFACE PLANETS