Researchers have developed cuTAMP, a novel task and motion planning algorithm leveraging GPU-accelerated parallel computing to enable robots to rapidly solve complex manipulation problems, such as packing and tool use, in seconds without requiring training data, demonstrably improving efficiency in industrial settings and offering broad applicability across robotic systems.
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