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Dist-GPRL is presented, a distance-aware and safety-guided reinforcement learning framework for structured robot skill adaptation that sequentially adapts overlapping local windows of sparse trajectory via-points rather than modifying the complete skill at every policy step.
Real-time dynamic object tracking and reconstruction is now possible with unprecedented accuracy using DisFlow's innovative distance field approach.
