mlsanityData to 7 Oct 2026

Research Challenges and Progress in Robotic Grasping and Manipulation Competitions

arXiv 2108.01483 ↗First posted 3 Aug 2021cs.RO cs.AIcited by 9

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Abstract (arXiv)

This paper discusses recent research progress in robotic grasping and manipulation in the light of the latest Robotic Grasping and Manipulation Competitions (RGMCs). We first provide an overview of past benchmarks and competitions related to the robotics manipulation field. Then, we discuss the methodology behind designing the manipulation tasks in RGMCs. We provide a detailed analysis of key challenges for each task and identify the most difficult aspects based on the competing teams' performance in recent years. We believe that such an analysis is insightful to determine the future research directions for the robotic manipulation domain.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 8 of its 52 references that are in the map. First posted on arXiv 3 Aug 2021.

Builds on

8 of 52 references.

References · 8

  1. 2018YouTube-VOS: Sequence-to-Sequence Video Object Segmentationcited by 228
  2. 2021OCRTOC: A Cloud-Based Competition and Benchmark for Robotic Grasping and Manipulationcited by 24
  3. 2020YCB-M: A Multi-Camera RGB-D Dataset for Object Recognition and 6DoF Pose Estimationcited by 12
  4. 2016The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to Foster Reproducible Researchcited by 11
  5. 2020Robot Gaining Accurate Pouring Skills through Self-Supervised Learning and Generalizationcited by 9
  6. 2020Benchmarking In-Hand Manipulationcited by 6
  7. 2020GRASPA 1.0: GRASPA is a Robot Arm graSping Performance benchmArkcited by 5
  8. 2019Robotic Materialscited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 3; 2024: 3; 2025: 0; 2026: 1.

9 papers.