LEASH: Stay Safe in Agentic Robotics
Overview
This paper introduces RoboRisk, a comprehensive benchmark for evaluating safety in agentic robotics, covering five categories across 92 simulated tasks and 13 physical-robot tasks. The authors evaluate six foundation models (GPT-6 Astra/Sol/Luna, Claude Opus 5.5, Gemini 4 Argon, Grok 4.7) and two robot APIs (Dream API, PokeBot's RoboAPI), finding high harm rates. They propose LEASH (Lease-Enforced Agentic Safety Harness), which uses a decision model to implement task, action, and commit gates in visual context, effectively reducing harm across all evaluated models while preserving task completion performance with minimal overhead.
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Reported quantity · tasks: 92 other · Basis not reported · Differing source assertions
“ng. We introduce RoboRisk, a comprehensive benchmark for evaluating safety in agentic robotics. Its 92 simulated tasks and 13 physical-robot tasks fall into five categories: Task-level Refusal (T), Plan Repair (P), Execution-time Hazard (E), Injection (I), and Sequential Memory (S). Prior benchmarks cover at most two of these categories, and several evaluate only text outputs. In contrast, RoboRisk covers all five an”
Exact source · revision 1Source owner not reported
Reported quantity · tasks: 13 other · Basis not reported · Differing source assertions
“ng. We introduce RoboRisk, a comprehensive benchmark for evaluating safety in agentic robotics. Its 92 simulated tasks and 13 physical-robot tasks fall into five categories: Task-level Refusal (T), Plan Repair (P), Execution-time Hazard (E), Injection (I), and Sequential Memory (S). Prior benchmarks cover at most two of these categories, and several evaluate only text outputs. In contrast, RoboRisk covers all five an”
Exact source · revision 1Source owner not reported
Reported quantity · Robot count: 2 robots · Basis not reported
“d executes every task in closed loop. We evaluate six state-of-the-art foundation models on RoboRisk: GPT-6 Astra, GPT-6.1 Sol, GPT-6 Luna, Claude Opus 5.5, Gemini 4 Argon, and Grok 4.7. These models generally show high harm rates. We also evaluate two robot-specific APIs: the Dream API and PokeBot's RoboAPI. We further propose the Lease-Enforced Agentic Safety Harness (LEASH), which offers essential safety infrastru”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalLEASH: Stay Safe in Agentic Robotics
This paper introduces RoboRisk, a comprehensive benchmark for evaluating safety in agentic robotics, covering five categories across 92 simulated tasks and 13 physical-robot tasks. The authors evaluate six foundation models (GPT-6 Astra/Sol/Luna, Claude Opus 5.5, Gemini 4 Argon, Grok 4.7) and two robot APIs (Dream API, PokeBot's RoboAPI), finding high harm rates. They propose LEASH (Lease-Enforced Agentic Safety Harness), which uses a decision model to implement task, action, and commit gates in visual context, effectively reducing harm across all evaluated models while preserving task completion performance with minimal overhead.
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