Multi-Robot Systems

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The field studies how robot teams can divide work, coordinate motion, and combine information to accomplish tasks that are difficult for one robot alone. Common approaches include multi-agent path finding and task allocation for warehouses and exploration, distributed control and reinforcement learning for swarms, and cooperative localization and SLAM that fuse cameras, ranging, and inertial sensors. Researchers also design communication protocols, simulators, and operator interfaces to support heterogeneous robots while managing limited bandwidth, computation, and human attention. A central challenge is making coordination safe and reliable as teams grow, robots fail, environments change, and methods move from simulation to real hardware.

Latest papers

205 papers30 papers in the last four weeks, up 76% on the four weeks before. 0.2% of all new papers.

SkySeg: Collaborative Onboard Semantic Segmentation with Heterogeneous UAVs in the Wild
May 20, 2026Anqi Lu, Yun Cheng, Youbing Hu +3Test-Time Adaptation Multi-Robot Systems
Harbin Institute of Technology Harbin, China · ETH Zurich Zurich, Switzerland · Huawei Cloud Algorithm Innovation Lab Be, China
Seeing Together: Multi-Robot Cooperative Egocentric Spatial Reasoning with Multimodal Large Language Models
May 18, 2026Kunyu Peng, Zhikun Zhou, Kailun Yang +9Visual Spatial Reasoning Multi-Robot Systems
Karlsruhe Institute of Technology · INSAIT, Sofia University “St. Kliment Ohridski” · Hunan University +4
Shared Backbone PPO for Multi-UAV Communication Coverage with Connection Preservation
May 18, 2026Z. JiangMulti-Robot Systems Proximal Policy Optimization
Zhejiang University
MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality
May 14, 2026Prakash Aryan, Cem Erdogdu, Kavinaya Kumarchokkappan +2Simultaneous Localization and Mapping Multi-Robot Systems
University of Bern, Bern, Switzerland · AI4I – The Italian Institute of Artificial Intelligence, Turin, Italy
A Prototyping Framework for Distributed Control of Multi-Robot Systems
May 14, 2026Junaid Ahmed Memon, Allan Andre Do Nascimento, Kostas Margellos +1Multi-Robot Systems Robotics Simulation
Department of Engineering Science, University of Oxford, UK
Uncertainty-Aware 3D Position Refinement for Multi-UAV Systems
May 13, 2026Hosam Alamleh, Damir PulatovMulti-Robot Systems UAV Navigation
Computer Science University of North Carolina Wilmington Wilmington, North Carolina, USA
Occlusion-Based Object Transportation Around Obstacles With a Swarm of Miniature Robots
May 13, 2026Breno Cunha Queiroz, Daniel MacRaeMulti-Robot Systems Swarm Robotics
Faculty of Science and Engineering, Rijksuniversiteit Groningen, Groningen, Netherlands. · Institute of Mathematics and Computer Sciences, University of S˜ao Paulo, S˜ao Carlos, S˜ao Paulo, Brazil.
Kairos: A Scalable Serving System for Physical AI
May 12, 2026Yinwei Dai, Ganesh Ananthanarayanan, Landon Cox +3Multi-Robot Systems Embodied AI
Princeton University · Microsoft
Distributed Pose Graph Optimization via Continuous Riemannian Dynamics
May 11, 2026Jaeho Shin, Maani Ghaffari, Yulun TianRiemannian Optimization Multi-Robot Systems
University of Michigan Ann Arbor, MI 48109, USA
MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction
May 11, 2026Zhihao Cao, Qi Shao, Shuhao Zhai +4Simultaneous Localization and Mapping 3D Gaussian Splatting
ETH Zurich, Switzerland · University of Liverpool, United Kingdom · Harbin Engineering University, China +4
Above and Below: Heterogeneous Multi-robot SLAM Across Surface and Underwater Domains
May 10, 2026John McConnell, Armon Shariati, Paul Szenher +1Simultaneous Localization and Mapping Multi-Robot Systems
United States Naval Academy, Annapolis, MD, USA · Shield-AI, San Diego CA, USA · Stevens Institute of Technology, Hoboken, NJ, USA
Minimizing Worst-Case Weighted Latency for Multi-Robot Persistent Monitoring: Theory and RL-Based Solutions
May 10, 2026Weizhen Wang, Ziheng Wang, Jianping He +2RL for Robotics Markov Decision Processes
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, China · Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China
PECMAN: Perception-enabled Collaborative Multi-Agent Navigation in Unknown Environments
May 10, 2026Tianchonghui Fang, Shaunak Roy, Shalabh GuptaMulti-Robot Motion Planning Multi-Robot Systems
Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA
CommandSwarm: Safety-Aware Natural Language-to-Behavior-Tree Generation for Robotic Swarms
May 8, 2026Mohammed Majid, Amjad Yousef MajidMulti-Robot Systems Swarm Robotics
Multi-Robot Coordination in V2X Environments
May 7, 2026John Pravin Arockiasamy, Alexey VinelMulti-Robot Systems Multi-Robot Coordination
*Karlsruhe Institute of Technology, Karlsruhe, Germany · †Halmstad University, Halmstad, Sweden
GA3T: A Ground-Aerial Terrain Traversability Dataset for Heterogeneous Robot Teams in Unstructured Environments
May 7, 2026Siwei Cai, Knut Peterson, Quan Tran +7Multi-Robot Systems Robot Traversability Estimation
Drexel University, Philadelphia, USA
Power-Efficiency and Scalability Analysis of Magnetically-Actuated Satellite Swarms via Convex Optimization
May 7, 2026Yuta Takahashi, Seang Shim, Hiraku Sakamoto +1Multi-Robot Systems Multi-Agent Control
Mechanical Engineering, Institute of Science Tokyo, Meguro-ku, Tokyo 152-8550, Japan · Department of Space and Astronautical Science, The Graduate University for Advanced Studies, Sagamihara, Kanagawa 252-5210, Japan · Spacecraft Engineering, Institute of Space and Astronautical Science, Sagamihara, Kanagawa 252-5210, Japan
Passive Fault Tolerance through Tension-to-Thrust Feed-Forward: Hybrid Input-to-State Stability for Decentralized Multi-UAV Slung-Load Transport under Abrupt Cable Severance
May 6, 2026Hadi Hajieghrary, Paul SchmittMulti-Robot Systems Robot Failure Recovery
Independent Researcher · Reynolds & Moore
Modular Reinforcement Learning For Cooperative Swarms
May 6, 2026Erel Shtossel, Gal A. KaminkaMulti-Robot Systems Reinforcement Learning
Bar Ilan University Ramat Gan, Israel
Say the Mission, Execute the Swarm: Agent-Enhanced LLM Reasoning in the Web-of-Drones
May 5, 2026Andrea Iannoli, Lorenzo Gigli, Luca Sciullo +2Aerial Robotics Multi-Robot Systems
Department of Computer Science and Engineering University of Bologna Bologna, Italy
AoI-Aware Multi-Robot Sensing and Transport on Connected Graphs
May 4, 2026John TadrousMulti-Robot Systems Age of Information
Electrical and Computer Engineering Department, Gonzaga University, WA 99258
Distributed Algorithm with Emergent Area Partitioning and Base Station's Situation Awareness for Multi-Robot Patrolling
May 2, 2026Kazuho Kobayashi, Shohei Kobayashi, Seiya Ueno +1Multi-Robot Systems Multi-Robot Coordination
Department of Mechanical Engineering, Materials Science, and Ocean Engineering, Graduate School of Engineering Science, Yokohama National University, Yokohama-city, Kanagawa, Japan · Faculty of Environment and Information Sciences, Yokohama National University
Decentralized Heterogeneous Multi-Robot Collaborative Exploration for Indoor and Outdoor 3D Environments
Apr 26, 2026Yuxiang Li, Kun Chen, Jiancheng Wang +3Multi-Robot Motion Planning Multi-Robot Systems
College of Artificial Intelligence, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China · Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hongkong 999077, China
Dynamic Coupling and Indirect Control of Jointed Robots Rolling Atop A Moving Platform
Apr 23, 2026Hamidreza Moradi, Scott David KellyRobotic Control Robot Trajectory Tracking
Department of Mechanical Engineering and Engineering Science, University of North Carolina at Charlotte, Charlotte, NC 28223 USA
Task-Driven Co-Design of Heterogeneous Multi-Robot Systems
Apr 23, 2026Maximilian Stralz, Meshal Alharbi, Yujun Huang +1Multi-Robot Systems
Laboratory for Information & Decision Systems, Massachusetts Institute of Technology, Cambridge, MA 02139
A Case Study in Recovery of Drones using Discrete-Event Systems
Apr 23, 2026Liam P. Burns, Dayse M. Cavalcanti, Felipe G. Cabral +4Dynamical Systems Aerial Robotics
Department of Electrical and Computer Engineering and Ingenuity Labs Research Institute, Queen’s University, Kingston, ON, K7L 3N6, Canada · Automation and Systems Engineering Program, Federal University of Santa Catarina, Florianópolis, SC, 88.040-900, Brazil
Effects of Swarm Size Variability on Operator Workload
Apr 23, 2026William Hunt, Aleksandra Landowska, Horia A. Maior +2Multi-Robot Systems Human-Robot Interaction
University of Southampton · University of Nottingham
PREVENT-JACK: Context Steering for Swarms of Long Heavy Articulated Vehicles
Apr 23, 2026Adrian Baruck, Michael Dubé, Christoph Steup +1Multi-Robot Systems Swarm Robotics
1*Chair of Computational Intelligence, Otto-von-Guericke-University, Universitätsplatz 2, Magdeburg, 39106, Germany. · 2Fraunhofer Institute for Transportation and Infrastructure Systems2026 IVI, Zeunerstr. 38, Dresden, 01069, Germany.
Navigating the Clutter: Waypoint-Based Bi-Level Planning for Multi-Robot Systems
Apr 22, 2026Jiabao Ji, Yongchao Chen, Yang Zhang +4RL for Robotics Multi-Robot Motion Planning
UC Santa Barbara · Massachusetts Institute of Technology · Harvard University +2
A Gesture-Based Visual Learning Model for Acoustophoretic Interactions using a Swarm of AcoustoBots
Apr 21, 2026Alex Lin, Lei Gao, Narsimlu Kemsaram +1Multi-Robot Systems Robotics
Department of Computer Science University College London London, United Kingdom · Department of Artificial Intelligence University of Malaya Kuala Lumpur, Malaysia

May 20, 2026J/K move · Enter open · S save

SkySeg: Collaborative Onboard Semantic Segmentation with Heterogeneous UAVs in the Wild

Anqi Lu, Yun Cheng, Youbing Hu, Zhiqiang Cao+2

Harbin Institute of Technology Harbin, China · ETH Zurich Zurich, Switzerland · Huawei Cloud Algorithm Innovation Lab Be, China

Test-Time Adaptation Multi-Robot Systems UAV Remote Sensing Semantic Segmentation

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The demand for unmanned aerial vehicle (UAV)-based image acquisition and analysis has surged, with UAVs increasingly utilized for semantic segmentation tasks. To meet the real-time analysis requirements of UAV remote sensing missions, performing onboard computation and making decisions based on the results is a natural approach. However, deploying semantic segmentation on resource-constrained UAV platforms presents two significant challenges: 1) hardware constraints limit the ability of UAVs to perform real-time semantic segmentation, and 2) environmental variations during flight cause data distribution shifts, deviating from the original training data. To address these issues, this paper introduces SkySeg, a heterogeneous multi-UAV air-air cooperation framework that integrates computer vision and flight pattern to enable onboard semantic segmentation using low-cost sensors. SkySeg employs an efficient information fusion inference method, combining low-definition, wide-area images with high-definition, focused-area images. Additionally, it incorporates a cross-device test-time adaptation (TTA) strategy to enhance segmentation performance in dynamic environments by collaboratively addressing distribution shifts of test data streams across UAVs. Experimental results demonstrate that our SkySeg framework accelerates inference latency by approximately 3.6x, improves onboard segmentation accuracy by 5.91%, and achieves a 10.91% average accuracy gain in the wild.