Robotic Manipulation

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Overview

Robotic manipulation studies how machines use sensing and motion to change objects and environments, from picking and assembly to tool use and handling deformable materials. Approaches combine geometric planning and force or impedance control with imitation learning, reinforcement learning, diffusion policies, and vision-language-action models; world models, memory, tactile feedback, and human-video demonstrations are also used. Methods are tested in simulation and on real robots using suites such as LIBERO, RoboTwin, ManiSkill, and RLBench, across clutter, bimanual coordination, mobile manipulation, and precision contact tasks. A central challenge is turning benchmark performance into safe, reliable long-horizon behavior across new objects, cameras, robot bodies, and real-world dynamics, while limiting data collection and inference costs.

Latest papers

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1,656 papers375 papers in the last four weeks, up 81% on the four weeks before. 2.1% of all new papers.

  1. Reward-Centered ReST-MCTS: A Robust Decision-Making Framework for Robotic Manipulation in High Uncertainty Environments

    Mar 7, 2025Xibai WangReward ShapingMonte Carlo Tree Search

    NeuroQuant Labs Limited Hong Kong SAR, China

  2. RetrDex: Efficient Object Retrieval in Cluttered Scenes with a Dexterous Hand

    Feb 25, 2025Fengshuo Bai, Yu Li, Jie Chu +5RL for RoboticsRobotic Manipulation

    Shanghai Jiao Tong University · PKU-PsiBot Joint Lab · Peking University +2

  3. 3D-MoE: Towards Spatial Intelligence with Mixture-of-Experts for 3D Reasoning and Action Generation

    Jan 28, 2025Yueen Ma, Zenglin Xu, Irwin King3D Spatial ReasoningMixture-of-Experts Inference

    Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR

  4. RoMu4o: A Robotic Manipulation Unit For Orchard Operations Automating Proximal Hyperspectral Leaf Sensing

    Jan 18, 2025Mehrad Mortazavi, David J. Cappelleri, Reza EhsaniRobotic GraspingRobotic Manipulation

    Department of Mechanical Engineering, University of California, Merced, CA, 95343, USA · School of Mechanical Engineering and Weldon School of Biomedical Engineering (By Courtesy), Purdue University, West Lafayette, IN USA 47907

  5. Data Scaling Laws in Imitation Learning for Robotic Manipulation

    Oct 24, 2024Fanqi Lin, Yingdong Hu, Pingyue Sheng +3Generalization in Robotic ManipulationRobotic Manipulation

    Tsinghua University · Shanghai Qi Zhi Institute · Shanghai Artificial Intelligence Laboratory

  6. Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation

    Apr 2, 2024Carlos Plou, Ana C. Murillo, Ruben Martinez-CantinModel-Based RLData-Efficient Robot Learning

    All authors are with the Instituto de Investigación en Ingeniería de Aragón (i3A) and DIIS, University of Zaragoza