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Coding Agents with an Obstacle-Aware Harness for Safe Robot Manipulation

Research LLM Agents

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TL;DR - SafeHarness improves the safety of coding agents for robot manipulation by separating obstacle-aware route planning from contact execution. It achieves 71.9% task success and 87.5% collision avoidance, outperforming the previous state of the art by 6.5 and 27.0 percentage points, respectively.

  • Baseline coding agents collided with obstacles in most cases despite recognizing them and receiving explicit instructions not to touch them.
  • The failure stemmed from planning: agents lacked clearing-route reasoning, replanning when routes became infeasible, and safety-aware contact selection.
  • SafeHarness represents objects as bounding boxes, generates and verifies waypoint routes, replans when needed, and chooses collision-free contact positions.
  • Compared with the same agent without the harnesses, task success increased by 2.3× and collision avoidance by 1.5×.

Sources (1)

Coding Agents with an Obstacle-Aware Harness for Safe Robot Manipulation

arXiv cs.RO Bingxin Xu, Yuzhang Shang, Zhen Dong, Emilio Ferrara 2026-09-17 arXiv:2609.20822
Public signals Semantic Scholar citations 0 · Semantic Scholar influential citations 0
Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · Citations 0 · Influential citations 0 X · N/A Fetched 2026-09-24 14:18:01.564569 UTC

TL;DR - SafeHarness improves the safety of coding agents for robot manipulation by separating obstacle-aware route planning from contact execution. It achieves 71.9% task success and 87.5% collision avoidance, outperforming the previous state of the art by 6.5 and 27.0 percentage points, respectively.

  • Baseline coding agents collided with obstacles in most cases despite recognizing them and receiving explicit instructions not to touch them.
  • The failure stemmed from planning: agents lacked clearing-route reasoning, replanning when routes became infeasible, and safety-aware contact selection.
  • SafeHarness represents objects as bounding boxes, generates and verifies waypoint routes, replans when needed, and chooses collision-free contact positions.
  • Compared with the same agent without the harnesses, task success increased by 2.3× and collision avoidance by 1.5×.
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