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A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder

2 Nov 2017arXiv:1711.00614archive 2025-07-28

Daehyung Park, Yuuna Hoshi, Charles C. Kemp

The detection of anomalous executions is valuable for reducing potential hazards in assistive manipulation. Multimodal sensory signals can be helpful for detecting a wide range of anomalies. However, the fusion of high-dimensional and heterogeneous modalities is a challenging problem. We introduce a long short-term memory based variational autoencoder (LSTM-VAE) that fuses signals and reconstructs their expected distribution. We also introduce an LSTM-VAE-based detector using a reconstruction-based anomaly score and a state-based threshold. For evaluations with 1,555 robot-assisted feeding executions including 12 representative types of anomalies, our detector had a higher area under the receiver operating characteristic curve (AUC) of 0.8710 than 5 other baseline detectors from the literature. We also show the multimodal fusion through the LSTM-VAE is effective by comparing our detector with 17 raw sensory signals versus 4 hand-engineered features.

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chickenbestlover/RNN-Time-series-Anomaly-Detection mentioned on GitHubpytorchApache-2.0 report
danyleb/variational-lstm-autoencoder mentioned on GitHubtfMIT report

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get_batch chickenbestlover/RNN-Time-series-Anomaly-Detection/1_train_predictor.py community (archive-listed) ran · our draft was wrong Apache-2.0 (permissive) · 566787f11a729568 · report
alphanum_key chickenbestlover/RNN-Time-series-Anomaly-Detection/png2gif.py community (archive-listed) unverified Apache-2.0 (permissive) · 052b2ec0f82abb8e · report
anomalyScore chickenbestlover/RNN-Time-series-Anomaly-Detection/anomalyDetector.py community (archive-listed) unverified Apache-2.0 (permissive) · 1ef6ff831cff2270 · report
fit_norm_distribution_param chickenbestlover/RNN-Time-series-Anomaly-Detection/anomalyDetector.py community (archive-listed) unverified Apache-2.0 (permissive) · cc97ebc512306ea0 · report
get_precision_recall chickenbestlover/RNN-Time-series-Anomaly-Detection/anomalyDetector.py community (archive-listed) unverified Apache-2.0 (permissive) · 5ae112cc846cc62e · report
normalization chickenbestlover/RNN-Time-series-Anomaly-Detection/preprocess_data.py community (archive-listed) unverified Apache-2.0 (permissive) · ebbdec7d25441eb9 · report
preprocess danyleb/variational-lstm-autoencoder/LstmVAE/prepare_data.py community (archive-listed) unverified MIT (permissive) · 78a18734bb0a2f00 · report
reconstruct chickenbestlover/RNN-Time-series-Anomaly-Detection/preprocess_data.py community (archive-listed) unverified Apache-2.0 (permissive) · 4b937bb49e947c19 · report
standardization chickenbestlover/RNN-Time-series-Anomaly-Detection/preprocess_data.py community (archive-listed) unverified Apache-2.0 (permissive) · 61729d480bdea1de · report
tryint chickenbestlover/RNN-Time-series-Anomaly-Detection/png2gif.py community (archive-listed) unverified Apache-2.0 (permissive) · 77ebbd9cfb0ed6a4 · report

Tasks

Anomaly Detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Anomaly Detection voraus-AD LSTM-VAE Avg. Detection AUROC 86.7 #2 of 3 Archive leaderboard report

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