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FINO-Net: A Deep Multimodal Sensor Fusion Framework for Manipulation Failure Detection
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<span title="2021-07-30">2021</span>
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arXiv
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<span class="release-stage" >pre-print</span>
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<span title="2020-11-11">2020</span>
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Safe manipulation in unstructured environments for service robots is a challenging problem. A failure detection system is needed to monitor and detect unintended outcomes. We propose FINO-Net, a novel multimodal sensor fusion based deep neural network to detect and identify manipulation failures. We also introduce a multimodal dataset, containing 229 real-world manipulation data recorded with a Baxter robot. Our network combines RGB, depth and audio readings to effectively detect and classify
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... ilures. Results indicate that fusing RGB with depth and audio modalities significantly improves the performance. FINO-Net achieves 98.60% detection and 87.31% classification accuracy on our novel dataset. Code and data are publicly available at https://github.com/ardai/fino-net.
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