Optimization scheme for dynamic obstacle recognition
For dynamic obstacle recognition, SpatialLM can be combined with other techniques:
- Timing Fusion:Fusion processing of continuous multi-frame point cloud data to recognize motion trajectories
- Semantic Filtering:Exclude typical static object categories and focus on detecting movable objects
- Multi-sensor fusion:Combined judgment with motion detection results in 2D vision
- Incremental Updates:Setting up a periodic rescanning mechanism to update the state of the environment
The best practice is to add a specialized motion detection module to the semantic annotation results of SpatialLM to form a dual verification mechanism.
This answer comes from the articleSpatialLM: Sweep the room, AI automatically draws 3D models for youThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of inaccurate recognition of dynamic obstacles in robot navigation?
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