mlsanityData to 7 Oct 2026

Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping

arXiv 2103.05401 ↗First posted 9 Mar 2021cs.RO cs.AIcited by 1

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Abstract (arXiv)

Robotic manipulation of unknown objects is an important field of research. Practical applications occur in many real-world settings where robots need to interact with an unknown environment. We tackle the problem of reactive grasping by proposing a method for unknown object tracking, grasp point sampling and dynamic trajectory planning. Our object tracking method combines Siamese Networks with an Iterative Closest Point approach for pointcloud registration into a method for 6-DoF unknown object tracking. The method does not require further training and is robust to noise and occlusion. We propose a robotic manipulation system, which is able to grasp a wide variety of formerly unseen objects and is robust against object perturbations and inferior grasping points.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 22 of its 44 references that are in the map. First posted on arXiv 9 Mar 2021.

Builds on

22 of 44 references.

References · 22

  1. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  2. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  3. 2019Deep Hough Voting for 3D Object Detection in Point Cloudscited by 648
  4. 2018Fast Online Object Tracking and Segmentation: A Unifying Approachcited by 272
  5. 2017Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metricscited by 259
  6. 2018Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objectscited by 237
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  9. 2018Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approachcited by 117
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  11. 20176-DoF Object Pose from Semantic Keypointscited by 89
  12. 2019Leveraging Shape Completion for 3D Siamese Trackingcited by 74
10 more
  1. 2019Antipodal Robotic Grasping using Generative Residual Convolutional Neural Networkcited by 59
  2. 2020Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Imagecited by 45
  3. 2018FilterReg: Robust and Efficient Probabilistic Point-Set Registration using Gaussian Filter and Twist Parameterizationcited by 43
  4. 2019Pose from Shape: Deep Pose Estimation for Arbitrary 3D Objectscited by 39
  5. 2017Real-time Perception meets Reactive Motion Generationcited by 30
  6. 2017SegICP: Integrated Deep Semantic Segmentation and Pose Estimationcited by 29
  7. 2015Probabilistic Object Tracking using a Range Cameracited by 21
  8. 2017Deep 6-DOF Trackingcited by 13
  9. 2019Tracking Holistic Object Representationscited by 9
  10. 2019Motion-Nets: 6D Tracking of Unknown Objects in Unseen Environments using RGBcited by 3

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Cited by year

Citing papers per year: 2023: 1.

1 paper.

  1. 2023TrackAgent: 6D Object Tracking via Reinforcement Learningcited by 1