いつ支援すべきか：支援ロボティクスにおける信頼性の高い人間意図予測のための校正済み信頼度
When to Act: Calibrated Confidence for Reliable Human Intention Prediction in Assistive Robotics
日常生活動作における次行動予測の信頼度を事後校正し、信頼度が高いときだけ支援を実行するACT/HOLDルールを提案した。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Johannes A. Gaus, Winfried Ilg, Daniel Haeufle
分類: cs.RO, cs.AI
原文アブストラクト
Assistive devices must determine both what a user intends to do and how reliable that prediction is before providing support. We introduce a safety-critical triggering framework based on calibrated probabilities for multimodal next-action prediction in Activities of Daily Living. Raw model confidence often fails to reflect true correctness, posing a safety risk. Post-hoc calibration aligns predicted confidence with empirical reliability and reduces miscalibration by about an order of magnitude without affecting accuracy. The calibrated confidence drives a simple ACT/HOLD rule that acts only when reliability is high and withholds assistance otherwise. This turns the confidence threshold into a quantitative safety parameter for assisted actions and enables verifiable behavior in an assistive control loop.
