What Stops Recursive Self-Improvement in Robotics? Lessons from 123 Rounds of Agentic Skill Discovery
Unlocking autonomous evolution in robotic systems through recursive skill discovery and iterative simulation testing.
Can a robot improve itself the way coding agents now improve software? We built an agentic system to find out. It watches a robot fail, works out which capability is missing, writes new skills or finds and installs external models, tests every change in simulation, and repeats, w...
ArXiv CS.RO
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The transition from static code generation to autonomous hardware refinement marks a critical shift in how robots overcome real-world physical constraints. By automating the trial-and-error cycle of skill discovery, researchers are narrowing the gap between theoretical agency and functional robotics.
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