Coding Agents with an Obstacle-Aware Harness for Safe Robot Manipulation
Coding agents have emerged as a promising paradigm for robot manipulation: a language model writes the robot controller as a program, and agents built in this way now operate robots without robot-specific training.Whether this paradigm is also safe, however, has not been asked. We evaluate coding agent under a safety constraint, where each task pairs a manipulation goal with an
Reading in Plain English mode — toggle below to switch
Coding agents have emerged as a promising paradigm for robot manipulation: a language model writes the robot controller as a program, and agents built in this way now operate robots without robot-specific training.Whether this paradigm is also safe, however, has not been asked. We evaluate coding agent under a safety constraint, where each task pairs a manipulation goal with an
This paper highlights a critical safety gap in current coding agents for robotics, where goal completion overrides safety constraints. For ML engineers, understanding how to integrate and prioritize safety in AI-driven control systems is crucial for deploying reliable and ethical robotic solutions.