mlsanityData to 7 Oct 2026

Mobile Robot Manipulation using Pure Object Detection

arXiv 2201.12437 ↗First posted 28 Jan 2022cs.CV cs.ROcited by 8

Not on the map. Why?

Abstract (arXiv)

This paper addresses the problem of mobile robot manipulation using object detection. Our approach uses detection and control as complimentary functions that learn from real-world interactions. We develop an end-to-end manipulation method based solely on detection and introduce Task-focused Few-shot Object Detection (TFOD) to learn new objects and settings. Our robot collects its own training data and automatically determines when to retrain detection to improve performance across various subtasks (e.g., grasping). Notably, detection training is low-cost, and our robot learns to manipulate new objects using as few as four clicks of annotation. In physical experiments, our robot learns visual control from a single click of annotation and a novel update formulation, manipulates new objects in clutter and other mobile settings, and achieves state-of-the-art results on an existing visual servo control and depth estimation benchmark. Finally, we develop a TFOD Benchmark to support future object detection research for robotics: https://github.com/griffbr/tfod.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 42 of its 71 references that are in the map. First posted on arXiv 28 Jan 2022.

Builds on

42 of 71 references.

References · 42

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  3. 2020End-to-End Object Detection with Transformerscited by 7,384
  4. 2017Mask R-CNNcited by 7,259
  5. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  6. 2019LVIS: A Dataset for Large Vocabulary Instance Segmentationcited by 1,215
  7. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 768
  8. 2016Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collectioncited by 312
  9. 2017CORe50: a New Dataset and Benchmark for Continuous Object Recognitioncited by 287
  10. 2020Frustratingly Simple Few-Shot Object Detectioncited by 280
  11. 2018Few-shot Object Detection via Feature Reweightingcited by 265
  12. 2019Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimationcited by 218
30 more
  1. 2015Supersizing Self-supervision: Learning to Grasp from 50K Tries and 700 Robot Hourscited by 208
  2. 2019Meta R-CNN : Towards General Solver for Instance-level Few-shot Learningcited by 182
  3. 2018Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networkscited by 171
  4. 2021FSCE: Few-Shot Object Detection via Contrastive Proposal Encodingcited by 168
  5. 2020Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wildcited by 142
  6. 2019TossingBot: Learning to Throw Arbitrary Objects with Residual Physicscited by 131
  7. 2021DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detectioncited by 106
  8. 2020Incremental Few-Shot Object Detectioncited by 102
  9. 2019Self-supervised 6D Object Pose Estimation for Robot Manipulationcited by 100
  10. 2021Generalized Few-Shot Object Detection without Forgettingcited by 88
  11. 2018RepMet: Representative-based metric learning for classification and one-shot object detectioncited by 85
  12. 2021Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detectioncited by 80
  13. 2021Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detectioncited by 79
  14. 2016Interactive Perception: Leveraging Action in Perception and Perception in Actioncited by 77
  15. 2018LSTD: A Low-Shot Transfer Detector for Object Detectioncited by 77
  16. 2021Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networkscited by 55
  17. 2021Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detectioncited by 53
  18. 2021Hallucination Improves Few-Shot Object Detectioncited by 50
  19. 2021Universal-Prototype Enhancing for Few-Shot Object Detectioncited by 43
  20. 2020OS2D: One-Stage One-Shot Object Detection by Matching Anchor Featurescited by 35
  21. 2017LabelFusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenescited by 32
  22. 2020Single View Metrology in the Wildcited by 20
  23. 2018CRAVES: Controlling Robotic Arm with a Vision-based Economic Systemcited by 18
  24. 2019Video Object Segmentation-based Visual Servo Control and Object Depth Estimation on a Mobile Robotcited by 14
  25. 2018Pay attention! - Robustifying a Deep Visuomotor Policy through Task-Focused Attentioncited by 11
  26. 2017Recognizing Objects In-the-wild: Where Do We Stand?cited by 10
  27. 2021Depth from Camera Motion and Object Detectioncited by 6
  28. 2020Real-time Grasp Pose Estimation for Novel Objects in Densely Cluttered Environmentcited by 5
  29. 2021Attention Guided Cosine Margin For Overcoming Class-Imbalance in Few-Shot Road Object Detectioncited by 3
  30. 2019Customizing Object Detectors for Indoor Robotscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 2; 2025: 2; 2026: 2.

8 papers.

  1. 2025InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policycited by 83
  2. 2026Being-H0.5: Scaling Human-Centric Robot Learning for Cross-Embodiment Generalizationcited by 61
  3. 2023Detect Everything with Few Examplescited by 13
  4. 2026ST4VLA: Spatially Guided Training for Vision-Language-Action Modelscited by 8
  5. 2023Kinematically-Decoupled Impedance Control for Fast Object Visual Servoing and Grasping on Quadruped Manipulatorscited by 1
  6. 2024OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair Navigationcited by 1
  7. 2025Auto-Labeling Data for Object Detectioncited by 1
  8. 2024Feedback-driven object detection and iterative model improvementcited by 0