SafeHarness: Obstacle-Aware Coding Agents for Robot Manipulation
This paper introduces SafeHarness, a method to improve the safety of coding agents in robot manipulation tasks. It addresses the critical issue where language models controlling robots prioritize task completion over avoiding obstacles, leading to collisions. SafeHarness equips these agents with obstacle-aware planning and execution capabilities.
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This paper introduces SafeHarness, a method to improve the safety of coding agents in robot manipulation tasks. It addresses the critical issue where language models controlling robots prioritize task completion over avoiding obstacles, leading to collisions. SafeHarness equips these agents with obstacle-aware planning and execution capabilities.
Imagine a chef trying to cook a meal (task goal) while blindfolded, with hot pans and sharp knives (obstacles) around. The chef knows not to touch them but only focuses on the recipe steps. SafeHarness is like giving the chef a spatial map and a planning assistant that says, 'First, move your hand here, avoiding the hot pan, then pick up the ingredient.' and 'When you cut, ensure the knife's path doesn't hit the edge of the counter.'
How SafeHarness Enhances Robot Safety
- 11. **Identify Failure Points**: The research first pinpoints why coding agents fail: they lack a notion of 'clearing routes' and replanning, and are unaware of safety constraints during contact execution.
- 22. **Obstacle-Aware Route Planning**: SafeHarness grounds objects as bounding boxes and plans routes as sequences of waypoints. The agent plans, verifies, and replans routes to avoid obstacles before execution.
- 33. **Obstacle-Aware Contact Execution**: During contact-rich moments, the system selects contact positions that inherently avoid obstacles, ensuring safety even in precise interactions.
- 44. **Improved Performance**: By integrating these two 'harnesses', the agent significantly improves both task success and collision avoidance, making robot manipulation safer and more reliable.
Safety Improvement Factor = Performance_with_Harness / Performance_without_Harness
This represents how much better the agent performs in terms of task success or collision avoidance when using SafeHarness compared to not using it. For task success, it's $2.3\times$ better, and for collision avoidance, $1.5\times$ better.
Consider a robot tasked with picking up a specific object on a table, but there's a delicate glass vase nearby. Without SafeHarness, the robot might plan a direct path, knocking over the vase. With SafeHarness, it first maps the vase's bounding box, plans a curved path around it, verifies the path, and only then executes the movement, ensuring the vase remains untouched.
Integrating explicit obstacle-aware planning and execution modules into coding agents is crucial for achieving safe robot manipulation, as language models alone often prioritize task completion over safety constraints.