Latest Robot Manipulation & VLA Research Papers

The newest Robot Manipulation & VLA papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Robot Manipulation & VLA so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.

Recent papers

• SwapBot: Tool-Centric Robot Manipulation via Interchangeable End-Effectors and Tactile Sensing
  Yunchu Zhang, Ray Song, Junhan Jiao, Liyiming Ke et al. · arXiv · Oct 29, 2026

  Robot manipulation in everyday environments inherently involves substantial tool usage. Seemingly simple household tasks, such as cooking pan-fried tofu, require forceful cutting, delicate brushing, and precise placement using different too…

• BURGER: Benchmarking and Understanding Robotic Generalization via Embodied Drawing
  Xiangyu Xu, Bangshuai Peng, Ziyi Liu, Mengjie Zhao et al. · arXiv · Oct 29, 2026

  How effectively can vision-language-action (VLA) models learn diverse language-conditioned behaviors as training data scales? Investigating this question requires large and varied robot datasets, whose collection on physical robots remains …

• Improving Fine-Grained Manipulation through Demonstration Expansion and Execution Design
  Jingxu Gu, Dongze Lian · arXiv · Oct 29, 2026

  Fine-grained manipulation requires a robot policy to follow instructions, remain robust to visual variations, and translate predicted actions into precise robot control. We present Demonstration Expansion and Execution Design (DEED), a fram…

• HiFOR: Hierarchical Foresight with Action-Guided World Grounding for Vision-Language-Action Model
  Rongxing Ding, Hongyu Qu, Kehong Wu, Xudong Wang et al. · arXiv · Oct 29, 2026

  Vision-Language-Action (VLA) models have demonstrated promising capabilities in robotic manipulation by integrating visual perception, language understanding, and action generation. Recent advances have further incorporated future predictio…

• JEDI: Joint-Embedding Demonstration Compression for In-Context Imitation Learning
  Jiazhao Liang, Zhewen He, Shuaihang Yuan, Hao Huang et al. · arXiv · Oct 29, 2026

  In-context imitation learning (ICIL) adapts robot policies through test-time demonstrations, but long multimodal trajectories constrain how many examples fit in context. We ask what a compressed demonstration should preserve. We propose JED…

• TouchBridge: Tactile-Conditioned Human-to-Robot Transfer for Dexterous Manipulation
  Haozhe Zhang, Gu Zhang, Zirui Zou, Yuzheng Chen et al. · arXiv · Oct 29, 2026

  Human demonstrations offer an efficient and scalable source of data for dexterous robot manipulation, but differences in sensing and hand morphology complicate the transfer of contact-rich interactions. We present TouchBridge, a hardware--s…

• Research on structural optimization and stable grasping control of flexible manipulators
  葉焜煌, WenWu Wang · Frontiers in Mechanical Eng... · Oct 28, 2026

  Introduction This paper designed an optimized pneumatic flexible manipulator with an embedded segmented hinge polylactic acid (PLA) skeleton and used an incremental proportional-integral-derivative (PID) closed-loop control strategy to impr…

• ThinkWorld: World Imagination Reinforces Chain-of-Dynamics Reasoning
  Chaehyun Kim, Chi-Pin Huang, Jisoo Kim, Min-Hung Chen et al. · arXiv · Oct 27, 2026

  Vision-Language-Action (VLA) models have made substantial progress in robotic manipulation, but their generalization remains constrained by the diversity and coverage of action-labeled robot demonstrations. Human videos provide much broader…

• Pushing Dexterity and Safety for In-Hand Object Pose Reaching That Works Remarkably Well
  Ian Chuang, Hiya Shah, Vamsi Chilamkur, Iman Soltani et al. · arXiv · Oct 27, 2026

  Dexterous manipulation with multi-fingered hands is the next frontier of robotics, yet learned hand skills remain limited to simple grasps or basic repeated motions, such as rotating an object. As robots attempt more demanding in-hand maneu…

• EgoThumb: A Vision-Driven Supernumerary Robotic Thumb for Autonomous Grasp and Holding Assistance
  Jianyu Hou, Jiawei Fu, Weikang Wan, Minghui Jiang et al. · arXiv · Oct 27, 2026

  Supernumerary robotic fingers augment human dexterity by enabling a single hand to perform complex "hold-and-manipulate" tasks that typically require bimanual coordination. However, existing devices are often hindered by bulky hardware that…

• Which Hand Was Late? Diagnosis for Robot Failure Recovery in Bimanual Tool Use
  Baptiste Bonin, Caro Strickland, Audrey Durand · arXiv · Oct 27, 2026

  Failure diagnosers for robot manipulation are increasingly vision--language models (VLMs), trained and evaluated on single-arm failures produced by perturbing a successful demonstration. Bimanual tool use adds failures of other kinds: a too…

• World Dreamer v5-lite: A Multi-Robot World Action Model with One Dreamer
  Guoning Wu, Zijian Cai, Yuhang Zhang, Ying Liu et al. · arXiv · Oct 27, 2026

  Multi-robot control requires integrating distributed camera views while predicting separate action sequences. Most vision-language-action and world-action models target one robot. Combining multiple views alone does not establish spatial co…

• Ego-CEVR: Learning Cross-Embodiment Visual Representations from Human Egocentric Videos
  Keru Zhou, Zhirui Fang, Xinrun Xu, Yaopeng Lou et al. · arXiv · Oct 27, 2026

  As egocentric video becomes increasingly available for embodied learning, an important research question is how to turn this low-cost, scalable source of data into robot manipulation capabilities. Egocentric videos naturally provide rich co…

• Learning Quality-Controllable Robot Policies with Iterative Hindsight Relabeling
  Sinjae Kang, Dong Kyu Shin, Jaehong Kim, Kamin Lee et al. · arXiv · Oct 27, 2026

  Robot policy evaluation often relies on a binary success signal for task completion. In real-world deployment, however, desired execution behaviors are also defined by quality attributes such as execution speed and motion smoothness, which …

• PDRVLA: A Vision-Language-Action Model with Physical Dynamics Representations
  Hanqing Wang, Zhaotian Cai, Ruichuan An, Bohan Zeng et al. · arXiv · Oct 27, 2026

  Vision--Language--Action (VLA) models generate robot actions from visual observations and language instructions, but their understanding of physical dynamics remains limited. Video world models can capture scene dynamics, yet generating fut…

• VLA-Stem: A Lightweight Safety Mechanism for Vision-Language-Action Models via Reinforcement Learning
  Bojun Zou, Wenhao Yu, Jiaohao Li, Jiaxuan Lin et al. · arXiv · Oct 27, 2026

  Vision-Language-Action (VLA) models integrate high-level reasoning with low-level action execution for end-to-end robotic control. However, most VLA models target static manipulation in unconstrained environments, overlooking spatial constr…

• Tokens of Motion: Primitive Motion Learning for Human-Humanoid Skill Transfer
  Hanwen Ren, Meng Zheng, Wenzhe Cui, Benjamin Planche et al. · arXiv · Oct 27, 2026

  Vision-language-action (VLA) models provide a promising paradigm for scalable robotic manipulation, yet their reliance on success-only behavioral cloning leaves them brittle; lacking corrective training signals, minor execution errors rapid…

• Vision-Language-Action or World-Action? Just Action Models
  Yonghao Yu, Lang Huang, Runyi Li, Toshihiko Yamasaki · arXiv · Oct 27, 2026

  The vision-language-action (VLA) and world-action model (WAM) communities debate whether control policies should inherit pretrained knowledge from vision-language models or from visual generators. The debate, however, bundles three separabl…

• Retrieve to Act: Motion Primitive Graph Retrieval for Robust VLA Execution
  Pham Tri Quang, Bao-Ngoc Dao, Minh Duc Nguyen, Duc-Duy Nguyen et al. · arXiv · Oct 27, 2026

  Vision-Language-Action (VLA) policies demonstrate remarkable semantic generalization, yet remain highly vulnerable to out-of-distribution (OOD) visual shifts during execution. While existing test-time methods attempt to suppress spurious vi…

• From 12 to 200 Demonstrations: How ACT, Diffusion Policy, SmolVLA and $π_{0.5}$ Scale on a Low-Cost Arm
  Simon Cowling · arXiv · Oct 27, 2026

  We trained four widely used imitation-learning policies, ACT, Diffusion Policy, SmolVLA and $π_{0.5}$, on nested subsets of 12, 25, 50, 100 and 200 teleoperated demonstrations of one pick-and-place task with distractor objects, using one fi…

• Vision-Language-Action Intelligence for Traditional Industrial Robotic Arms
  Weijian Wan · Applied and Computational E... · Oct 27, 2026

  Vision-language-action (VLA) intelligence provides a unified route for connecting visual perception, language understanding, and executable control in traditional industrial robotic arms. This paper examines the transition from modular perc…

• BSSA-net: category-level 6D object pose estimation with bi-scale and semantic-aligned feature interaction
  蔡同慶, Wenjun Zhu, Yang Yi, Mengyi Zhang et al. · Robotic Intelligence and Au... · Oct 27, 2026

  Purpose Category-level 6D object pose estimation is essential for robotic grasp detection and manipulation. However, large distribution gaps between synthetic and real data, the limited capacity of single-branch architectures to capture mul…

• Tactile Perception for Embodied Intelligent Dexterous Hands: Sensor Principles, Sensor Placement, and Multimodal Fusion
  Xiaoyi Gong · Applied and Computational E... · Oct 27, 2026

  To perform these movements better, dexterous hands need to be able to feel contact with objects and the surrounding environment. This article mainly introduces tactile technology for dexterous hands, and it discusses these technologies from…

• Artificial Intelligence and Robotics for Automated Pharmacy and Medicine Dispensing Systems: A Survey
  Abhijith T S, D H Aromal, S Nasif, Nithul Das H et al. · IJARCCE · Oct 27, 2026

  Manual medicine dispensing, drug storage, and pharmacy inventory management remain error-prone, slow, and labor-intensive, motivating a rapid rise in artificial intelligence (AI) and robotics research aimed at automating these processes.Thi…

• Profiling a Frontier Agent with EBench: From Direct Control to Harness with Policy
  Yifei Yao, Yude Zou, Guanbo Jiao, Xing Gao et al. · arXiv · Oct 26, 2026

  Frontier multimodal large language models (MLLMs) can control robots without robot-specific training, but how their capabilities compare and interact with post-trained vision-language-action (VLA) and world action model (WAM) policies acros…

• Pretraining Knows What, Simulation Teaches How: Compositional Generalization in a Sim-Trained Robot Agent
  Benjamin Pikus, Daniel Saunders, Mircea Mironenco, Salman Mohammadi et al. · arXiv · Oct 26, 2026

  A robot policy needs to understand what a task is asking for in a scene, and how to move the robot to accomplish that task. To achieve these two skills, we introduce Zero-real Agent Policy (ZAP), a recipe that teaches a small off-the-shelf …

• VPR-Space: A Benchmark for Visual Place Recognition in Space Analog Domains
  Richard Fechner, Peer Neubert · arXiv · Oct 26, 2026

  Visual Place Recognition (VPR) is an important means for loop closure detection in visual Simultaneous Localization and Mapping (SLAM). While state-of-the-art VPR and SLAM approaches excel in urban and feature-rich natural environments, the…

• Robot-Aligned 3D Gaussian Splatting for Precise Reaching with Wrist-Camera VLA Policies
  Zuoxu Wang, Xiao Liang · arXiv · Oct 26, 2026

  Efficient robotic data collection remains a major bottleneck for vision-language-action (VLA) policy learning, especially for tasks requiring accurate end-effector positioning and camera-action alignment. This challenge is particularly seve…

• DEX-PHD: A Dexterous Portable Handheld Device for Multimodal Data Collection
  Jooyoung Hong, Noboru Myers, Obin Kwon, Yixian Yang et al. · arXiv · Oct 26, 2026

  Existing manipulation data collection methods typically offer either accurate robot-state acquisition through kinematic-chain-based teleoperation or convenient, portable operation through vision-based approaches. We present DEX-PHD, a porta…

• Benchmark-path fidelity in parallel robot-policy evaluation: a CALVIN case study
  Yuanzhi He, Qiming Wang, Jiayu Xu · The Journal of Supercomputing · Oct 24, 2026

  Abstract Evaluating long-horizon robot manipulation policies is a high-throughput computing workload: one CALVIN-style campaign sweeps checkpoints, seeds and task sequences across many concurrent simulator workers, consuming tens of thousan…