HRIBench: New Benchmark for Human-Robot Interaction Reveals Gaps in Current Robot Policies

Jul 16, 2026

Researchers have introduced HRIBench, a benchmark designed to evaluate vision-language-action (VLA) models in collaborative human-robot interaction scenarios. HRIBench features 13 tasks and over 650 episodes, focusing on intent understanding, temporal coordination, and safety in shared agency settings. Evaluations show that current robot policies such as GR00T and pi0.5 perform well in manipulation but struggle significantly with collaborative and interaction-centric tasks. Fine-tuning on HRIBench data improves collaborative performance, and simulation data from the benchmark has been shown to enhance real-world task success rates for robots.

Why it matters: HRIBench exposes critical shortcomings in current robot policies for real-world collaboration and provides a new tool for advancing interaction-aware robot learning.

Full story at: arXiv Robotics ↗