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%.
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Signal-backed technical analysis will be available soon.
| Metric | P2M | kwx | AgenticFORGE | whos-there |
|---|---|---|---|---|
| Stars | 76 | 76 | 76 | 77 |
| Forks | 8 | 12 | 5 | 6 |
| Weekly Growth | -1 | +0 | +0 | +0 |
| Language | Python | Python | TypeScript | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | BSD-3-Clause | NOASSERTION | MIT |
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.