New Safety Framework Aims to Mitigate Robot Failures in Homes
A recent study published on arXiv (2608.05313) proposes a safety framework designed to assess both the likelihood and impact of significant interactions between service robots and their surroundings during failure scenarios. This methodology allows robots to strategically plan by weighing safety against operational efficiency. Additionally, the authors introduce FailBench, a simulation framework based on MuJoCo, which examines robot-environment interactions across various failure types, including sensory malfunctions. This research acknowledges the inevitability of robot failures in domestic settings shared with humans, pets, and common objects, with the goal of reducing potential risks for safe and dependable usage. The paper is categorized as a cross-type announcement and can be accessed at arXiv:2608.05313.
Key facts
- Paper arXiv:2608.05313 introduces a novel safety formulation for service robots.
- The formulation evaluates both probability and severity of impactful interactions during failures.
- The approach enables robots to balance safety with task efficiency in planning decisions.
- FailBench, a MuJoCo-based simulation framework, is presented for studying robot-environment interactions.
- FailBench supports diverse failure modes, including sensing issues.
- Service robots are susceptible to software crashes, hardware degradation, and unpredictable interactions.
- The research aims to mitigate consequences of inevitable robot failures in household environments.
- The paper is a cross-type announcement on arXiv.
Entities
Institutions
- arXiv