GrandTour dataset paper releases large-scale ANYmal-D legged-robot perception data
Evidence notes
- The GrandTour paper introduces a large open-access legged-robotics dataset for state estimation, SLAM, perception, and multi-modal learning.
- The dataset was collected with an ANYbotics ANYmal-D quadruped carrying the Boxi multi-modal sensor payload across indoor and outdoor environments.
- The dataset gives ANYmal-D a large-scale public benchmark for legged-robot perception, state estimation, SLAM, and multi-modal learning.
Company context
ANYbotics develops autonomous legged robots for industrial inspection in complex and hazardous environments. Its ANYmal platform targets repeatable monitoring, inspection and safety workflows.