VLA RobustnessIntermediate
Is Success All You Need? Investigating the Impact of Input Perturbations on VLA Behaviour in Tabletop Manipulation Tasks
This arXiv preprint introduces a benchmark-agnostic evaluation framework that measures how successful VLA-controlled trajectories change under input perturbations, going beyond task success rate. Testing three state-of-the-art VLA models across four LIBERO suites and seven perturbation conditions, it finds that perturbed trajectories can still succeed yet diverge substantially in motion smoothness, efficiency, and gripper behaviour. This matters because teams relying only on success rate may miss behavioural degradation that affects safety and reliability.