mlsanityData to 14 Oct 2026

The Developments and Challenges towards Dexterous and Embodied Robotic Manipulation: A Survey

arXiv 2507.11840 ↗First posted 16 Jul 2025cs.ROcited by 4

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Abstract (arXiv)

Achieving human-like dexterous robotic manipulation remains a central goal and a pivotal challenge in robotics. The development of Artificial Intelligence (AI) has allowed rapid progress in robotic manipulation. This survey summarizes the evolution of robotic manipulation from mechanical programming to embodied intelligence, alongside the transition from simple grippers to multi-fingered dexterous hands, outlining key characteristics and main challenges. Focusing on the current stage of embodied dexterous manipulation, we highlight recent advances in two critical areas: dexterous manipulation data collection (via simulation, human demonstrations, and teleoperation) and skill-learning frameworks (imitation and reinforcement learning). Then, based on the overview of the existing data collection paradigm and learning framework, three key challenges restricting the development of dexterous robotic manipulation are summarized and discussed.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Jul 2025.

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Citing papers per year: 2025: 1; 2026: 3.

4 papers.

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  1. 2025Dexterous Manipulation through Imitation Learning: A Survey
  2. 2025Interactive Imitation Learning for Dexterous Robotic Manipulation: Challenges and Perspectives -- A Survey
  3. 2024Survey of Learning-based Approaches for Robotic In-Hand Manipulation
  4. 2025Towards Human-level Dexterity via Robot Learning
  5. 2025Robotic Manipulation via Imitation Learning: Taxonomy, Evolution, Benchmark, and Challenges
  6. 2022Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation
  7. 2025ManipTrans: Efficient Dexterous Bimanual Manipulation Transfer via Residual Learning
  8. 2026Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration