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Robots can now navigate crowded spaces more effectively by understanding human intentions, thanks to a new method that integrates rich visual cues into their decision-making process.
Realistic pedestrian simulations can significantly improve the training and evaluation of human-aware navigation systems, bridging the gap between simulated and real-world interactions.
Current single-view mesh reconstruction methods falter under robot camera rotations, leading to critical errors in spatial reasoning.
