Multi-Robot Coordination

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Multi-robot coordination studies how robots with shared or complementary goals work together in settings such as exploration, transport, warehouses, and aerial-ground missions. Approaches include task allocation and scheduling, joint or distributed motion planning, formation and feedback control, and learned policies that use local observations, communication, or demonstrations. Work increasingly combines these methods with safety constraints, uncertainty-aware replanning, and language or vision models, with evaluation spanning simulation, benchmarks, and physical robot teams. A central challenge is balancing the efficiency and global awareness of centralized planning against the scalability, resilience, and limited communication of decentralized teams, especially when robots or environments differ from those seen in training.

Latest papers

328 papers50 papers in the last four weeks, up 22% on the four weeks before. 0.3% of all new papers.

Speed-Weighted Adaptive Flocking for Sailing Swarms under Dynamic Environmental Forcing
May 19, 2026Pranav Kedia, Aaron Gan, Hannah J. Williams +2Swarm Robotics Robotics Simulation
Centre for the Advanced Study of Collective Behaviour, Konstanz, Germany · Dep. of Computer and Information Science, University of Konstanz, Germany · University of Pittsburgh, Pittsburgh, USA +2
Learning-Accelerated Optimization-based Trajectory Planning for Cooperative Aerial-Ground Handover Missions
May 19, 2026Jingshan Chen, Bochen Yu, Henrik Ebel +1Multi-Robot Motion Planning Trajectory Optimization
Institute of Engineering and Computational Mechanics, University of Stuttgart, 70569 Stuttgart, Germany · Mechanical Engineering, LUT University, 53850 Lappeenranta, Finland
Self-assembling Modular Aerial Robot for Versatile Aerial Tasks
May 19, 2026Junichiro Sugihara, Masaki Kitagawa, Jinjie Li +4Aerial Robotics Modular Robotics
Department of Mechanical Engineering, The University of Tokyo,Tokyo, Japan. · Department of Mechano Informatics, The University of Tokyo,Tokyo, Japan.
Orchestrating Wheeled Mobile Robots Online without Conflicts
May 18, 2026Jianghong Dong, Yifeng Zhang, Wenhan Cao +4Multi-Robot Formation Control Multi-Robot Motion Planning
School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China · Department of Mechanical Engineering, National University of Singapore, 117575, Singapore · Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109, USA
Distributed 3D Leader-Follower Formation Control with Field-of-View Safety via Control Barrier Functions
May 17, 2026Immanuel R. Santjoko, Richie R. Suganda, Miao Pan +1Multi-Robot Formation Control Aerial Robotics
Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77004, USA · Department of Engineering Technology, University of Houston, Houston, TX 77004, USA
HCLM: A Hierarchical Framework for Cooperative Loco-Manipulation with Dual Quadrupeds
May 17, 2026Qixuan Li, Chen Le, Jincheng Yu +1Whole-Body Control Multi-Task Robotic Manipulation
Shenzhen International Graduate School, Tsinghua University, Shenzhen, China. · Department of Electronic Engineering, and the Institute for Embodied Intelligence and Robotics, Tsinghua University, Beijing, China.
Task Capability Improvement Algorithm for Collaborative Manipulators
May 17, 2026Keshab Patra, Arpita Sinha, Anirban GuhaRobotic Control Multi-Robot Coordination
Department of Mechanical Engineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India · Center for Systems and Control, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India
Multi-Agent Cooperative Transportation: Optimal and Efficient Task Allocation and Path Finding
May 15, 2026Ning Zhou, Nikolai W. F. Bode, Edmund R. HuntMulti-Agent System Optimization Multi-Robot Coordination
University of Bristol
Propagating Unsafe Actions in LLM Controlled Multi-Robot Collaboration via Single Robot Compromise
May 15, 2026Zhen Huang, Zhihuang Liu, Mengxuan Luo +2Large Language Model-Based Robot Planning Adversarial Attacks on LLMs
College of Computer Science and Technology, National University of Defense Technology
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.
Coordinated Diffusion: Generating Multi-Agent Behavior Without Multi-Agent Demonstrations
May 12, 2026Lasse Peters, Laura Ferranti, Andrea Bajcsy +1Multi-Agent Coordination Diffusion Policy
University of California, Berkeley · Delft University of Technology · Carnegie Mellon University
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
A Cross-Layered Multi-Drone Coordination for Medical Supply Delivery during Disaster Response Management
May 10, 2026Aneesh Calyam, Subrahmanya Chandra Bhamidipati, Zack Murry +1Aerial Robotics UAV Navigation
University of Missouri–Columbia, Columbia, MO 65211, USA
Omni-scale Learning-based Sequential Decision Framework for Order Fulfillment of Tote-handling Robotic Systems
May 9, 2026Jiaxin Liu, Peng Yang, Yuping Li +1Combinatorial Optimization Robotics
Institution of Data and Information, Shenzhen International Graduate School, Tsinghua University, Nanshan District, Shenzhen 518055, China
AirBender: Adaptive Transportation of Bendable Objects Using Dual UAVs
May 7, 2026Jiawei Xu, Longsen Gao, Rafael Fierro +1Robot Trajectory Tracking Aerial Robotics
Autonomous and Intelligent Robotics Laboratory (AIRLab), Lehigh University, PA, 18015, USA · Electrical and Computer Engineering Department, The University of New Mexico, Albuquerque, NM, 87131, USA
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
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
LLM-Foraging: Large Language Models for Decentralized Swarm Robot Foraging
May 2, 2026Peihan Li, Joanna Gutierrez, Fabian Hernandez +2Swarm Robotics Language Model-Based Control
Drexel University, Philadelphia, PA 19104, USA · The University of Texas Rio Grande Valley, Edinburg, Texas 78541, USA
Topology-Driven Anti-Entanglement Control for Soft Robots
May 1, 2026Haoyang Le, Shengxuan Wang, Mohan Chen +1Multi-Robot Coordination Soft Robotics
School of Mathematics and Statistics, Zhengzhou University, No. 100 Science Avenue, Zhengzhou, 450001, Henan, China · School of Computer Science and Artificial Intelligence, Zhengzhou University, No. 100 Science Avenue, Zhengzhou, 450001, Henan, China · College of Information Engineering, North China University of Water Resources and Electric Power, No. 136 Jinshui East Road, Jinshui District, Zhengzhou, 450046, Henan, China
Sensitivity-Based Tube NMPC for Cooperative Aerial Structures Under Parametric Uncertainty
Apr 28, 2026Giuseppe Silano, Quentin Sablé, Marco Tognon +2Aerial Robotics Nonlinear MPC
Ricerca sul Sistema Energetico S.p.A., Milan, Italy, and Czech Technical University, Prague, Czechia · University of Twente, Enschede, The Netherlands · University of Rennes, CNRS, Inria, IRISA, 35042, France +2
Slot-hopping Enabled Loiter Guidance and Automation for Fixed-wing UAV Corridors
Apr 28, 2026Pradeep J, Siddhardha Kedarisetty, Ashwini RatnooUAV Navigation Multi-Robot Coordination
Indian Institute of Technology Bhilai, Bhilai, 491002, India · Indian Institute of Science, Bengaluru, 560012, India
Optimal UGV-UAV Cooperative Partitioning and Inspection of Shortest Paths
Apr 28, 2026Ninh Nguyen, Srinivas AkellaCompetitive Analysis UAV Navigation
Dynamic UGV-UAV Cooperative Path Planning in Uncertain Environments
Apr 28, 2026Ninh Nguyen, Srinivas AkellaMulti-Robot Motion Planning Multi-Robot Coordination
Department of Computer Science, University of North Carolina at Charlotte, NC 28223, USA
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
DM $^3$ -Nav: Decentralized Multi-Agent Multimodal Multi-Object Semantic Navigation
Apr 23, 2026Amin Kashiri, Atharva Jamsandekar, Yasin YazıcıoğluVision-Language Navigation Multi-Robot Coordination
Northeastern University, Boston, USA · Department of Electrical and Computer Engineering at Northeastern University, Boston, MA
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
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.
Multi-UAV Path Following using Vector-Field Guidance
Apr 20, 2026Gautam Kumar, Amit Shivam, Ashwini RatnooMulti-Robot Formation Control Collision Avoidance
Department of Aerospace Engineering, Indian Institute of Science Bangalore, India 560012 · Department of Electrical and Computer Engineering, University of Porto, Porto, Portugal
Shepherding UAV Swarm with Action Prediction Based on Movement Constraints
Apr 19, 2026Yusuke Tsunoda, Yusuke Goto, Takao SatoSwarm Robotics UAV Navigation
Graduate School of Engineering, University of Hyogo, Hyogo, Japan

May 19, 2026J/K move · Enter open · S save

Speed-Weighted Adaptive Flocking for Sailing Swarms under Dynamic Environmental Forcing

Pranav Kedia, Aaron Gan, Hannah J. Williams, Andreagiovanni Reina+1

Centre for the Advanced Study of Collective Behaviour, Konstanz, Germany · Dep. of Computer and Information Science, University of Konstanz, Germany · University of Pittsburgh, Pittsburgh, USA+2

Swarm Robotics Robotics Simulation Robotics Multi-Robot Coordination

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Collective behavior models, such as aggregation and flocking, usually assume self-propelled robots that can directly execute their desired speed and direction of motion without fundamental constraints. However, autonomous sailing robots violate this assumption. Their motion is shaped by wind-dependent propulsion, restricted headings, and spatially varying wind conditions. In particular, maneuverability is coupled to wind speed: in weak wind, sailboats may turn only slowly or not at all, whereas stronger wind enables faster turns. This introduces transient heterogeneity in speed and maneuverability across the flock. We focus on this fast-slow coordination problem in sailing robot flocks. To study this problem, we introduce SailSwarmSwIM, a reduced-order simulator for autonomous sailing robot swarms that captures wind-dependent speed and maneuverability, no-go zones, tacking behavior, and steady or gusty wind fields. To design our novel flocking technique, we start from the Couzin model and introduce a speed-weighted social interaction rule that accounts for each robot's transient motion constraints. A key result is that increasing the social influence of slower robots improves polarization and reduces close encounters. This effect arises from a balance between attraction to fast neighbors, which helps maintain movement, and cohesion around slow neighbors, which prevents the flock from fragmenting. Together, our simulator, SailSwarmSwIM, and the speed-weighted interaction rule provide a modeling framework for studying adaptive collective behavior in robotic fleets whose motion capabilities are continuously shaped by wind.