Robotic Manipulation

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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

1,685 papers341 papers in the last four weeks, up 29% on the four weeks before. 2.0% of all new papers.

Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation
Jun 2, 2026Litao Liu, Yifan Han, Pengfei Yi +9Language-Conditioned Robot Manipulation Robotic Manipulation
Department of Computer Science, Rutgers University-New Brunswick · The Hong Kong University of Science and Technology (GZ) · Shanghai AI Laboratory
SimuScene: Simulation-Ready Compositional 3D Scene Reconstruction from a Single Image
Jun 2, 2026Inhee Lee, Sangwon Baik, Sungjoo Kim +33D Reconstruction Robotics Simulation
Seoul National University
Preference-Calibrated Human-in-the-Loop Reinforcement Learning for Robotic Manipulation
Jun 2, 2026Zeyi Liu, Guangyao Liu, Yinuo Qu +6Credit Assignment in RL Robotic RL
Central South University · Nanyang Technological University · Zhejiang University
PointAction: 3D Points as Universal Action Representations for Robot Control
Jun 2, 2026Mutian Tong, Han Jiang, Qiao Feng +2Generalization in Robotic Manipulation Cross-Embodiment Robot Learning
University of Pennsylvania · Work done during internship at University of Pennsylvania.
WorkBenchMark: A LEGO-Based Assembly Benchmark with an Assembly-by-Disassembly Baseline for the Smart Manufacturing League
Jun 2, 2026Wenbo Ma, Daniel Swoboda, Matteo Tschesche +1Robotic Manipulation Robot Task Planning
Chair of Machine Learning and Reasoning (i6), RWTH Aachen University, Aachen, Germany · MASCOR Institute, FH Aachen University of Applied Sciences, Aachen, Germany
Revisiting Embodied Chain-of-Thought for Generalizable Robot Manipulation
Jun 2, 2026Nan Sun, Yuan Zhang, Yongkun Yang +10Long-Horizon Robotic Manipulation CoT Reasoning
Tsinghua University · Xiaomi Robotics · Peking University +6
PHASER: Phase-Aware and Semantic Experience Replay for Vision-Language-Action Models
Jun 2, 2026Ziyang Chen, Shaoguang Wang, Weiyu Guo +5Continual Learning for VLA Models Robotic Manipulation
Thrust of AI, HKUST(Guangzhou), Guangzhou, China · AI2 Robotics, Shenzhen, China
OpenEAI-Platform: An Open-source Embodied Artificial Intelligence Hardware-Software Unified Platform
Jun 2, 2026Jinyuan Zhang, Luoyi Fan, Leiyu Wang +4Robotic Control Compliant Robot Control
1Shanghai Innovation Institute · 2Huazhong University of Science and Technology · 3Shanghai Jiao Tong University +1
Grasp-Then-Plan with Failure Attribution: A Closed Two-Stage Framework for Precise and Generalizable Robotic Manipulation
Jun 2, 2026Jiahao Xu, Peiyuan Wang, Hanzhuo Zhang +8Robotic Grasping Long-Horizon Robotic Manipulation
School of Computer Science and Engineering, Southeast University, China
SplitAdapter: Load-Aware Humanoid Loco-Manipulation via Factorized Adaptation
Jun 2, 2026Jeonguk Kang, Hanbyel Cho, Sanghyun Kang +1Synthetic-to-Real Domain Adaptation Humanoid Loco-Manipulation
Future Robot AI Group, Samsung Electronics
Toward Gripper-Integrated Active Electrosense for Pre-Contact Sensing in Underwater Soft Grippers
Jun 2, 2026Ahsan Tanveer, Muhammad Hamza, Waqar Hussain Afridi +2Active Sensing Robotic Manipulation
Intelligent Biomimetic Design Lab, School of Advanced Manufacturing and Robotics, and with the State Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, Beijing 100871, China · National Engineering Research Center of Software Engineering, Peking University, Beijing 100871, China · Institute of Ocean Research, Peking University, Beijing 100871, China
ConTrack: Constrained Hand Motion Tracking with Adaptive Trade-off Control
Jun 2, 2026Yutong Liang, Quanquan Peng, Ri-Zhao Qiu +1Robot Trajectory Tracking Long-Horizon Robotic Manipulation
University of California San Diego
RoboDream: Compositional World Models for Scalable Robot Data Synthesis
Jun 1, 2026Junjie Ye, Rong Xue, Basile Van Hoorick +6Robot Skill Learning Robot Demonstration Generation
1USC Physical Superintelligence (PSI) Lab · 2Toyota Research Institute
AFUN: Towards an Affordance Foundation Model for Functionality Understanding
Jun 1, 2026Zhaoning Wang, Yi Zhong, Jiawei Fu +2Generalization in Robotic Manipulation Language-Conditioned Robot Manipulation
University of Michigan · University of California, San Diego · NVIDIA
Intercepting the Future: Latent-Space Predictive World Model for Dynamic VLA Manipulation
Jun 1, 2026Shahram Najam Syed, Arthur Jakobsson, Haoran Hao +1World Models for Robotics Robotic Manipulation
Robotics Institute, Carnegie Mellon University, Pittsburgh, USA
Dexterity-BEV: Aligning 3D World and Actions for Generalizable Robot Policies Learning
Jun 1, 2026Huayi Zhou, Wei Gao, Dekun Lu +12Generalization in Robotic Manipulation Cross-Embodiment Robot Learning
1DexForce Technology · 2The Chinese University of Hong Kong, Shenzhen
Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects
Jun 1, 2026Jens U. Kreber, Lukas Mack, Joerg Stueckler3D Gaussian Splatting Dynamical Systems
Intelligent Perception in Technical Systems Group, University of Augsburg, Augsburg, Germany
Set-Supervised Diffusion Policy: Learning Action-Chunking Diffusion through Corrections
Jun 1, 2026Zhaoting Li, Gang Chen, Javier Alonso-Mora +2Diffusion Policy Robotic Manipulation
Delft University of Technology · University of Stuttgart
The Lie We Tell: Correcting the Euclidean Fallacy in Vision Language Action Policies via Score Matching on Tangent Space
Jun 1, 2026Bing-Cheng Chuang, I-Hsuan Chu, Bor-Jiun Lin +3Lie Group Methods Robotic Manipulation
Department of Computer Science and Information Engineering & Artificial Intelligence Center of Research Excellence, National Taiwan University, Taipei, Taiwan · Institute of Artificial Intelligence Innovation, National Yang Ming Chiao Tung University, Hsinchu, Taiwan · Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan.
FlipItRight: Stable Pose-Targeted Throw-Flip Across Diverse Objects
Jun 1, 2026Axel Dawne, Shinkyu ParkNon-Prehensile Manipulation Robot Motion Generation
King Abdullah University of Science and Technology (KAUST), Saudi Arabia
S2M-Trek: From Single to Multi-Sphere Transport via Per-Frame Deep Sets on a Wheel-Legged Robot
May 31, 2026Zong Chen, Xuebin Li, Jinpeng Xiao +5Robotic Loco-Manipulation Representation Learning
School of Mechanical Science and Engineering, Huazhong University of Science and Technology · School of Mathematics, Harbin Institute of Technology
OneVLA: A Unified Framework for Embodied Tasks
May 31, 2026Lingfeng Zhang, Xiaoshuai Hao, Yingbo Tang +10Vision-Language Navigation Robotic Manipulation
1Tsinghua University · 3Xiaomi EV · Institute of Automation, Chinese Academy of Sciences +3
Implicit Drifting Policy: One-Step Action Generation via Conditional Expert Geometry
May 31, 2026Zemin Yang, Yaoyu He, Yiming Zhong +5Robot Policy Learning Imitation Learning
ShanghaiTech University · Shanghai Jiao Tong University · The Chinese University of Hong Kong +1
Learning Multi-Modal Trajectory Policies for Data-Efficient Robotic Manipulation
May 31, 2026Zijia Chen, Yuenan Hou, Xinhua Jiang +3Robot Policy Learning Mixture of Experts
College of Electronic Science and Technology, National University of Defense Technology Changsha, 410073, China · Shanghai AI Laboratory Shanghai, 200000, China
$τ_0$ -WM: A Unified Video-Action World Model for Robotic Manipulation
May 31, 2026Pengfei Zhou, Shengcong Chen, Di Chen +17Action-Conditioned Video Generation Long-Horizon Robotic Manipulation
1Shanghai Innovation Institute · 2AGIBOT Finch
Threading Optimization for Vision-Language-Action Model Inference in Low-Cost Smart Agricultural Manipulation
May 31, 2026Keith Truongcao, Christopher Nhu, Zijian An +3Efficient VLA Model Inference Robotic Manipulation
Department of Electrical Engineering, Drexel University, Philadelphia, USA
SafeVLA-Bench: A Benchmark for the Success-Safety Gap in Vision-Language-Action Models
May 30, 2026Jialiang Fan, Weizhe Xu, Zijun Wang +3Robot Safety Robotic Manipulation
University of Notre Dame · University of Pennsylvania
PACE: Phase-Aware Chunk Execution for Robot Policies with Action Chunking
May 30, 2026Junnan Nie, Jiayi Li, Chenghao Liu +5Robotic Manipulation Action Chunking
Peking University · Peking University. · JD Explore Academy. +1
Haptic Sorter: A Unified Planning Framework for Online Shape Estimation and Real-Time Pose Inference
May 29, 2026Zhuoyi Lu, Lin Yang, Sri Harsha Turlapati +1Tactile Sensing Object Pose Estimation
School of Mechanical and Aerospace Engineering, Nanyang Technological University (NTU), Singapore
Surface Constraint Policy for Learning Surface-Constrained and Dynamically Feasible Robot Skills
May 29, 2026Shuai Ke, Jiexin Zhang, Huan Zhao +4Contact-Rich Robotic Manipulation Diffusion Policy
State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China

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Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation

Litao Liu, Yifan Han, Pengfei Yi, Wenbo Yu+8

Department of Computer Science, Rutgers University-New Brunswick · The Hong Kong University of Science and Technology (GZ) · Shanghai AI Laboratory

Language-Conditioned Robot Manipulation Robotic Manipulation Robot Manipulation Benchmarks Affordance-Based Robotic Manipulation

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Task-conditioned manipulation requires grounding instructions to task-relevant functional parts rather than object categories. This setting is scene-dependent and often one-to-many in cluttered scenes: the same object may afford different interactions across tasks, while a single task may correspond to either one functional region or multiple valid functional regions, depending on the scene layout. Existing affordance datasets and benchmarks remain misaligned with this setting, as they typically focus on grasping or object-level affordances, rely on synthetic scenes, or assume a single instruction-region correspondence. We present Affordance2Action (A2A), a benchmark-centered learning framework for scene-level, task-conditioned part affordance grounding. At its core is A2A-Bench, a manipulation-oriented benchmark that covers both single-region and multi-region instruction correspondences in everyday scenes, with the latter highlighting the ambiguity and diversity of affordance grounding in realistic multi-object environments. To construct it at scale, we build A2A-AffordGen, an agent-assisted annotation pipeline that combines language-model filtering, interactive part segmentation, instance-level mask-out refinement, task-reasoning instruction generation, and human verification. A2A-Bench's supervision further supports diverse downstream applications, with real-time affordance grounding and affordance-conditioned manipulation policies as two representative examples. Experiments show that A2A exposes substantial gaps in generic segmentation, VLM-based grounding, and affordance distillation baselines, while improving task-level localization and providing useful spatial priors for downstream manipulation.