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SCOD: Active Object Detection for Embodied Agents using Sensory Commutativity of Action Sequences

arXiv 2107.02069 ↗First posted 5 Jul 2021cs.LG cs.ROcited by 0

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Abstract (arXiv)

We introduce SCOD (Sensory Commutativity Object Detection), an active method for movable and immovable object detection. SCOD exploits the commutative properties of action sequences, in the scenario of an embodied agent equipped with first-person sensors and a continuous motor space with multiple degrees of freedom. SCOD is based on playing an action sequence in two different orders from the same starting point and comparing the two final observations obtained after each sequence. Our experiments on 3D realistic robotic setups (iGibson) demonstrate the accuracy of SCOD and its generalization to unseen environments and objects. We also successfully apply SCOD on a real robot to further illustrate its generalization properties. With SCOD, we aim at providing a novel way of approaching the problem of object discovery in the context of a naive embodied agent. We provide code and a supplementary video.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 31 references that are in the map. First posted on arXiv 5 Jul 2021.

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15 of 31 references.

References · 15

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2017Mask R-CNNcited by 7,259
  3. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  4. 2020RAFT: Recurrent All-Pairs Field Transforms for Optical Flowcited by 2,385
  5. 2015FlowNet: Learning Optical Flow with Convolutional Networkscited by 1,054
  6. 2020Mastering Atari with Discrete World Modelscited by 990
  7. 2018Recurrent World Models Facilitate Policy Evolutioncited by 761
  8. 2019Video Object Segmentation using Space-Time Memory Networkscited by 436
  9. 2020iGibson 1.0: a Simulation Environment for Interactive Tasks in Large Realistic Scenescited by 151
  10. 2020STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videoscited by 121
  11. 2015Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocolscited by 98
  12. 2016Interactive Perception: Leveraging Action in Perception and Perception in Actioncited by 77
3 more
  1. 2019Building an Affordances Map with Interactive Perceptioncited by 6
  2. 2017Learning to Singulate Objects using a Push Proposal Networkcited by 5
  3. 2020On the Sensory Commutativity of Action Sequences for Embodied Agentscited by 3

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