Week 10 — MAPPO Training Pipeline and Environment Finalization

Finalized the MARL environment, set up the MAPPO training pipeline, and replanned the schedule after falling ~2 weeks behind.

Milestones

• Finalized GGSwarmMarlEnv — multi-agent Crazyflie spawning, observation/action spaces, distance-based graph connectivity, and reward shaping
• Set up MAPPO training pipeline in SKRL, validated via phase1_demo.py
• Replanned Phase 2 — ~2 weeks behind the original Mar 3 target, but back on track to complete within days

Next Steps

• Complete Phase 2: Brain Development by training the GATv2 coordination policy
• Transition into Phase 3: Muscle Refinement — MINCO trajectory optimization and SwarmRaft decentralized consensus

Challenges

The sheer complexity of integrating Isaac Lab, PyTorch Geometric, SKRL, and MARL — all while learning them from scratch. Breaking through those integration hurdles has been tough but rewarding.