Contact-rich Manipulation

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

10 shown of 10 papers with code (61 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning
  4 Feb 2024 2 repositories listed Syntology ran 8 of 9 samples · 1 unverified
  These outcomes suggest that the 3D point cloud is a valuable observation modality for intricate robotic tasks.
• Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones
  29 Oct 2020 2 repositories listed Syntology ran 4 of 4 samples · 0 unverified
  Safety remains a central obstacle preventing widespread use of RL in the real world: learning new tasks in uncertain environments requires extensive exploration, but safety requires limiting exploration.
• Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks
  24 Oct 2018 2 repositories listed Syntology ran 0 of 11 samples · 11 unverified · 2 pointer-only (licence)
  Contact-rich manipulation tasks in unstructured environments often require both haptic and visual feedback.
• Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation
  4 Mar 2025 1 repository listed
  Furthermore, most teleoperation systems struggle to provide fine-grained tactile / force feedback, which limits the range of tasks that can be performed.
• Learning Variable Compliance Control From a Few Demonstrations for Bimanual Robot with Haptic Feedback Teleoperation System
  21 Jun 2024 1 repository listed
  Our methods have been validated across various complex contact-rich manipulation tasks using single-arm and bimanual robot setups in simulated and real-world environments, demonstrating the effectiveness of our system…
• Accelerating Robot Learning of Contact-Rich Manipulations: A Curriculum Learning Study
  27 Apr 2022 1 repository listed
  The Reinforcement Learning (RL) paradigm has been an essential tool for automating robotic tasks.
• A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation
  9 Nov 2021 1 repository listed Syntology ran 1 of 3 samples · 2 unverified
  Specifying tasks with videos is a powerful technique towards acquiring novel and general robot skills.
• Reinforcement Learning for Contact-Rich Tasks: Robotic Peg Insertion Strategies
  14 Dec 2020 1 repository listed
  In this project, to connect vision and touch, we first equip robots with both visual and tactile sensors and collect a large-scale dataset of corresponding vision and tactile sequences.
• Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks
  28 Jul 2019 1 repository listed
  Contact-rich manipulation tasks in unstructured environments often require both haptic and visual feedback.
• Learning from the Hindsight Plan -- Episodic MPC Improvement
  28 Sep 2016 1 repository listed
  To bring the next real-world execution closer to the hindsight plan, our approach learns to re-shape the original cost function with the goal of satisfying the following property: short horizon planning (as realistic…

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.