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Eugene Mironov
2afe107583
Implement Real-Time Chunking (RTC) for action chunking policies using flow matching denoising. RTC enables smooth action transitions between consecutive chunks by using prefix guidance during denoising. Key features: - RTCProcessor class with denoise_step method for RTC guidance - Tracker system for debug tracking using time-based dictionary storage - RTCDebugVisualizer with comprehensive visualization utilities - Integration with SmolVLA policy for flow matching models - Support for multiple prefix attention schedules (ZEROS, ONES, LINEAR, EXP) - Configurable execution horizon and max guidance weight - Example scripts for dataset evaluation and real-time control Technical details: - Uses autograd-based gradient computation for RTC corrections - Time-based tracking eliminates duplicate step issues - Proxy methods in RTCProcessor for cleaner API - Full integration with LeRobot's policy and dataset systems Files added/modified: - src/lerobot/configs/types.py: Add RTCAttentionSchedule enum - src/lerobot/policies/rtc/: Core RTC implementation - configuration_rtc.py: RTC configuration - modeling_rtc.py: RTCProcessor with denoise_step - debug_handler.py: Tracker for debug information - debug_visualizer.py: Visualization utilities - src/lerobot/policies/smolvla/modeling_smolvla.py: RTC integration - examples/rtc/: Example scripts and evaluation tools 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Alexander Soare <alexander.soare159@gmail.com> Co-Authored-By: Claude <noreply@anthropic.com>