SensoryScape Height Change Algorithm Trial Data for Mobile LiDAR

A dataset of real-world testing for LiDAR-based stair and elevation change detection. It was created by Nikhil Herdt and published on figshare in May 2026. The dataset is stored in an XLSX file and is 18.0 KB in size.

Use Cases

• Benchmark stair detection algorithms based on LiDAR sensor data.
• Evaluate elevation change detection performance on consumer mobile hardware.
• Train machine learning models for terrain-aware navigation.
• Validate sensor fusion algorithms for real-world obstacle detection.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• It contains real-world testing data, likely reflecting practical performance.
• The file is small (18.0 KB), facilitating quick download and inspection.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (18.0 KB), indicating a limited scope or sample size.

Provenance

Source

figshare

Collection Method

Real-world testing for LiDAR-based detection.

Freshness

Last updated 2026-05-05 18:11:49; freshness should be verified.