paperAugust 2026Unreviewed

Agentic Harnesses: LLM-Driven Verification Layers for Robot Autonomy

Rohan Bhagra, Mahantesh Halapannavar, Uddhav Bhattarai

Abstract

Advances in advanced artificial intelligence tools have sparked research in robot autonomy, but the development of such systems has largely focused on execution rather than verifying the feasibility actions planning models propose. Like general-purpose LLMs, robotics planning models carry risks: biased toward user-specified goals, they may suggest actions misaligned with scientific ethics, they may be unsafe due to an inability to"remember"prior safety risks, or they may be vulnerable to adversa

Cite

@misc{bhagra2026agentic,
  title = {{Agentic Harnesses: LLM-Driven Verification Layers for Robot Autonomy}},
  author = {Rohan Bhagra and Mahantesh Halapannavar and Uddhav Bhattarai},
  year = {2026},
  month = aug,
  eprint = {2608.09857},
  archivePrefix = {arXiv},
  url = {https://www.semanticscholar.org/paper/5f39fb04dbe12b5f64ec64252d2c570e3fb9fe0d}
}