RACE: Calibrated Cumulative Scoring for Rollout-Free Robot Policy Checkpoint Selection
Overview
This paper presents RACE, a new metric for selecting robot policy checkpoints without costly real-world trials. Unlike averaged validation loss, which can misrank checkpoints, RACE calibrates action deviations against state-conditional thresholds derived from successful trajectories. By aggregating scores via a running product, it reduces the impact of early deviations on subsequent predictions. Experiments in simulation and on real robots show that RACE outperforms baselines across various policy backbones and tasks, with rankings aligning well with deployment success.
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- arXiv Robotics — research abstractsSignalRACE: Calibrated Cumulative Scoring for Rollout-Free Robot Policy Checkpoint Selection
This paper presents RACE, a new metric for selecting robot policy checkpoints without costly real-world trials. Unlike averaged validation loss, which can misrank checkpoints, RACE calibrates action deviations against state-conditional thresholds derived from successful trajectories. By aggregating scores via a running product, it reduces the impact of early deviations on subsequent predictions. Experiments in simulation and on real robots show that RACE outperforms baselines across various policy backbones and tasks, with rankings aligning well with deployment success.
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Current attention 3·Peak within the comparable range 9（2026-11-05 07:00 UTC）·Change within the comparable range over 24 hours -49%
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