Aeroact

Follow this topic Ask about this topic

Momentum

4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Jul 13Week of Sep 28

Latest papers 28

All topics

AeroManip-VLA: Scalable Vision-Language-Action Learning for Aerial Manipulation with RL-Generated Demonstrations
Sep 29, 2026Rui Huang, Yanlin Mu, Lidong Li +3Aerial Manipulation Diffusion-Based Vision-Language-Actions
National University of Singapore · Beijing Institute of Technology
Knowing When Thinking Is Not Enough: Teaching Small Reasoning Models to Reason Beyond Their Parametric Knowledge
Sep 28, 2026Chanuk Lee, Minki Kang, Sangwoo Park +3Small Reasoning Model Test Time
KAIST
AeroWeaver: An Embodied-Agent Harness for Weaving Aerial Skills into Distributed, Adaptive Swarm Execution
Sep 16, 2026Jiabin Lou, Yirong Yang, Haopeng Wang +6Unmanned Aerial Vehicle Swarms Swarms
Beihang University, 37 Xueyuan Road, Haidian District, Beijing 100191, China
Dual-Layer Semantic-Spatial Belief Mapping for Aerial Object Goal Navigation
Sep 8, 2026Jianqiang Xiao, Xiang Deng, Yuexuan Sun +3Aerial Vision-Language Navigation Aeroact
IEEE TRANSACTIONS ON MULTIMEDIA
Aero Hand Open: A Simulation-Ready Tendon-Driven Hand for Dexterous Manipulation Learning
Aug 28, 2026Nan Wang, Mohit Yadav, Jonathan Wulff +5Robotic Hands Motion Control
Chestnut Robotics
Causal Behavioral Evaluation of AI Agents at Scale via Automated Behavioral Science
Aug 10, 2026Soo Yong Lee, Jongha Lee, Jaewan Chun +8Artificial Intelligence Agents Automated
KAIST, Kim Jaechul Graduate School of AI · Yale, Department of Psychiatry · University of Haifa, School of Public Health +3
AeroReformer2: Spoken-Query Referring Segmentation for Aerial Images
Aug 9, 2026Rui Li, Chenxi Duan, Haoyang YangRemote Sensing Image Segmentation Remote Sensing
Aero Realtime: Fully Aligned Input-Output Streams for Low-Latency Streaming Multimodal Generation
Aug 9, 2026Kaichen Zhang, Wei Huang, Keming Wu +2Multimodal Generation Streaming
1The University of Hong Kong · 2LMMs-Lab · 3Tsinghua University
AeroDPO: Unleashing Lightweight UAV Navigation with High-Fidelity Perception and Automated Preference Optimization
Aug 2, 2026Peng Xu, Chengcheng Wang, Shaohua WanAerial Vision-Language Navigation Unmanned Aerial Vehicles
University of Electronic Science and Technology of China, Chengdu, China · 2Shenzhen Institute for Advanced Study, UESTC, Shenzhen, China
AeroLLE: Constrained Pseudo-Supervision for Nighttime Aerial Image Enhancement with the AeroNight-1.5K Benchmark
Aug 1, 2026Wei Lu, Hongyuan Liu, Si-Bao ChenLow-Light Image Enhancement Aeroact
MOE Key Lab of ICSP, IMIS Lab of Anhui, Anhui Provincial Key Lab of Multimodal Cognitive Computation, Zenmorn-AHU · AI Joint Lab, School of Computer Science and Technology, Anhui University, Hefei 230601, China
AeroAct: Action-Centered World-Action Models for Language-Conditioned Quadrotor Flight
Jul 16, 2026Xinhong Zhang, Qiyuan Zhu, Yubo Huang +8Aerial Vision-Language Navigation Quadrotor
School of Automation, Beijing Institute of Technology · School of Mechanical Engineering, Beijing Institute of Technology · Independent researcher
UAV-OVVIS: Unmanned Aerial Vehicles Also Need Open-Vocabulary Video Instance Segmentation
Jul 9, 2026Mingyu Dou, Shi Qiu, Ming Hu +2Drone Detection Video Object Segmentation
Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Institute of Artificial Intelligence (TeleAI), China Telecom +2
AeroVerse-SatAgent: UAV-Satellite Collaborative Spatial Reasoning Inspired by the Dual Visual Pathway Theory of Cognitive Neuroscience
Jun 30, 2026Wenyi Zhang, Fanglong Yao, Youzhi Liu +5Spatial Reasoning Multiple Satellite Systems
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China · University of Chinese Academy of Sciences, Beijing 100190, China · School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100190, China +4
AERIS: Aerial-Edge Role-Driven Intelligence at Runtime via Orchestrated Language-Model Swarm
Jun 29, 2026Jiabin Lou, Haopeng Wang, Xinyu Liu +3Aerial Vision-Language Navigation Aerial Robots
School of Computer Science and Engineering, Beihang University, Beijing 100191, China · Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, China · School of Artificial Intelligence, Beihang University, Beijing 100191, China
AeroCast: Probabilistic 3D Trajectory Prediction for Non-Cooperative Aerial Obstacles via Transformer-MDN Architecture
Jun 23, 2026Syed Izzat Ullah, Jose BacaSpatiotemporal Prediction Aeroact
Department of Engineering, Texas A&M University–Corpus Christi, Corpus Christi, TX 78412 USA
EgoAERO: Learning Dexterous Manipulation from a Single Egocentric Video without Object Assets
Jun 6, 2026Yichen Niu, Haoran Lv, Xinrui Zhang +12Contact-Rich Dexterous Manipulation Dexterous Manipulation
School of Astronautics, Harbin Institute of Technology · 2Lumos Robotic · 3Suzhou Research Institute, Harbin Institute of Technology +5
Mechanistic Interpretability for Learning Assurance of a Vision-Based Landing System
May 20, 2026Romeo Valentin, Olivia Beyer Bruvik, Marc R. Schlichting +1Aeroact Mechanistic Interpretability
Stanford Intelligent Systems Laboratory, Stanford University, Stanford, CA, USA
Explainable Wastewater Digital Twins: Adaptive Context-Conditioned Structured Simulators with Self-Falsifying Decision Support
May 19, 2026Gary Simethy, Daniel Ortiz Arroyo, Petar DurdevicDigital Twins Cognitive Digital Twins
Department of Energy, Aalborg University, Niels Bohrs Vej 8, Esbjerg, 6700, Denmark
Aero-World: Action-Conditioned Aerial Video Generation from Inertial Controls
May 19, 2026Abdul Mohaimen Al Radi, Kunyang Li, Yuzhang Shang +2Camera-Conditioned Video Generation Aeroact
Institute of Artificial Intelligence, University of Central Florida
Reinforcement Learning for Optimal Experiment Design in Parameter Identification of Mechatronic Systems
May 19, 2026Julian Langschwert, Georg Schaefer, Jakob Rehrl +2System Identification Reinforcement Learning Control
Josef Ressel Centre for Intelligent and Secure Industrial Automation, Salzburg University of Applied Sciences, Salzburg, Austria · Paris Lodron University of Salzburg, Salzburg, Austria
A World Model of Radiologist Reading for Medical Image Representation Learning
May 17, 2026Yiwei Li, Zihao Wu, Huaqin Zhao +5Medical Images Radiology Report Generation
University of Georgia · University of Texas at Arlington · New Jersey Institute of Technology
AERO-VIS: Asynchronous Event-based Real-time Onboard Visual-Inertial SLAM
May 8, 2026Yannick Burkhardt, Sebastián Barbas Laina, Simon Boche +2Visual Inertial Odometry Simultaneous Localization And Mapping
Mobile Robotics Lab, ETH Zürich · Technical University of Munich · Munich Center for Machine Lerning (MCML) +1
AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling
May 7, 2026Francisco Giral, Abhijeet Vishwasrao, Andrea Arroyo Ramo +8Aerodynamics Queryable Sector Flow Fields
Universidad Politécnica de Madrid · University of Michigan · Universitat Politècnica de València +3
AeroBridge-TTA: Test-Time Adaptive Language-Conditioned Control for UAVs
Apr 21, 2026Lingxue LyuAeroact Unmanned Aerial Vehicles
University of Pennsylvania Philadelphia, Pennsylvania, United States
AeroRAG: Structured Multimodal Retrieval-Augmented LLM for Fine-Grained Aerial Visual Reasoning
Apr 20, 2026Junxiao Xue, Quan Deng, Tingqi Hu +4Knowledge-Based Visual Question Answering Multimodal Retrieval Augmented Generation
Research Center for Space Computing System, Zhejiang Lab, Hangzhou 311100, China · Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 311000, China · School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou 450002, China +1
Safer Trajectory Planning with CBF-guided Diffusion Model for Unmanned Aerial Vehicles
Apr 19, 2026Peiwen Yang, Shiyu Bai, Weisong Wen +2Diffusion Planning Unmanned Aerial Vehicle Trajectories
Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong
AeroDeshadow: Physics-Guided Shadow Synthesis and Penumbra-Aware Deshadowing for Aerospace Imagery
Apr 17, 2026Wei Lu, Zi-Yang Bo, Fei-Fei Sang +3Single Image Dehazing Aerial Imagery
MOE Key Laboratory of ICSP, IMIS Laboratory of Anhui, Anhui Provincial Key Laboratory of Multimodal Cognitive Computation, Zenmorn-AHU AI Joint Laboratory, School of Computer Science and Technology, Anhui University, Hefei 230601, China · School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China
AeroGrab: A Unified Framework for Aerial Grasping in Cluttered Environments
Mar 16, 2026Shivansh Pratap Singh, Naveen Sudheer Nair, Samaksh Ujjawal +4Aerial Manipulation Robotic Grasping
Robotics Research Center, IIIT Hyderabad, India. · Department of Computer Science, University of Manchester, UK.

Sep 29, 2026, cs.ROJ/K move · Enter open · S save

AeroManip-VLA: Scalable Vision-Language-Action Learning for Aerial Manipulation with RL-Generated Demonstrations

Rui Huang, Yanlin Mu, Lidong Li, Yucong Wang+2

National University of Singapore · Beijing Institute of Technology

Aerial Manipulation Diffusion-Based Vision-Language-Actions Aerial Robots Aeroact

Open paper AskPDF arXiv

Aerial manipulators extend robotic manipulation into 3D workspaces that are difficult for ground-based robots to access, creating new opportunities for general-purpose manipulation. However, extending Vision-Language-Action (VLA) models to aerial robots introduces distinct challenges due to the tight coupling between manipulation and flight, continuously changing observations, and safety-critical physical interactions. These challenges demand diverse training data and systematic policy evaluation, yet collecting demonstrations and evaluating policies directly on physical aerial platforms are costly, difficult to scale, and hard to repeat under controlled conditions. We present AeroManip-VLA, a scalable benchmark for aerial VLA data generation and policy evaluation. AeroManip-VLA provides a GPU-accelerated simulation framework with low-level payload-aware flight and manipulation control in massively parallel environments. Building on this framework, we combine reusable reinforcement learning policies with expert task rules to automatically generate demonstrations without human teleoperation across diverse objects, environments, and randomized initial conditions. The generated data include basic skills such as grasping and placing, as well as long-horizon tasks that require both navigation and manipulation. We further introduce automated event labeling and trajectory categorization to filter demonstrations. These mechanisms enable fine-grained analysis of task progress, behavioral outcomes, and safety-related failures. Finally, we evaluate a range of imitation learning and VLA baselines across different task settings, revealing their performance characteristics and failure modes. Together, AeroManip-VLA enables scalable aerial manipulation data generation, structured trajectory analysis, and systematic VLA evaluation in simulation prior to real-world deployment.

Momentum

Related topics

Latest papers 28