P2

arclab-hku/P2M

[RA-L'25] A Simple LiDAR-centric End-to-end Navigation Framework in Dynamic Environments

76 8 -1/wk
GitHub
dynamic-obstacle-avoidance end-to-end-navigation reinforcement-learning
Trend 0

Star & Fork Trend (9 data points)

Stars
Forks

Multi-Source Signals

Growth Velocity

arclab-hku/P2M has -1 stars this period . 7-day velocity: -1.3%.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric P2M kwx AgenticFORGE whos-there
Stars 76 767677
Forks 8 1256
Weekly Growth -1 +0+0+0
Language Python PythonTypeScriptPython
Sources 1 111
License MIT BSD-3-ClauseNOASSERTIONMIT

Capability Radar vs kwx

P2M
kwx
Maintenance Activity 100

Last code push 1 days ago.

Community Engagement 53

Fork-to-star ratio: 10.5%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under MIT. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.