AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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MAESTRO is used as a coding agent that writes robot programs using a curated library of perception, planning, and control tools and its orchestration harness packages multi-step perception and action procedures into callable tools and guides their use through a plan–act– replan loop.
Laplacian editing is combined with simulation-based trajectory optimization to generalize across object poses, and a residual reinforcement learning policy refines the interaction forces by adjusting the reference pose of the underlying admittance controller.
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