Comparing Indoor Localization Systems

Work In Progress

LiDAR-SLAM

Pros

• Can be simultaneously used for obstacle detection/avoidance as well.
• Robust detection in most indoor and outdoor environments (except for reflective or transparent surfaces and the like)
• Does not require any modification of navigation environment.

Cons

• Expensive
  • Even the cheapest hobby grade LiDAR sensors cost hundreds of dollars. For example the RPLIDAR.
  • More reliable industrial grade LiDAR sensors cost several thousand dollars each. For example Hokuyo Range finders.
  • Off the shelf integrated systems for localization relying on LiDAR often cost tens of thousands of dollars each.
• High processing requirements. Most available LiDAR-SLAM systems require a dedicated computer and runs on CPU.
• No global reference.
  • Localization errors inevitably accumulate along with odometry drift.
  • Most systems can mitigate odometry drift from bundle adjustments and loop closure techniques only to an extent.
  • Environments with repetitive features generate many false positives.
• For robust operation, manually mapping the environment is required prior to localization.
  • Even then, initial location guess required in most current systems.

Visual-SLAM

Pros

Cons

• inaccurate
• sensitive to ambient conditions

Motion Capture Cameras

• expensive

HTC Vive Lighthouse

• bulky

Ultra Wide Band (UWB)

• inaccurate
• requires accurate beacon locations
• systems are not portable countries to do differing wireless spectrum regulations.

Eye in sky camera

• cheap
• centralized pattern recognition doesn't scale
• network latency
• requires line of sight
• limited area
• sensitive to ambient conditions
• require calibration

AR codes