Multi-Robot Navigation in Unknown Environments

Latest papers

15 papers2 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Capability-Conditioned Graph Control Barrier Functions for Zero-Shot Safe Navigation of Heterogeneous Mobile Robot Teams
Oct 30, 2026Joonkyung Kim, Janghyun Cho, Jeehyun Lee +2Multi-Robot Navigation in Unknown Environments Multi-Robot Systems
Dept. of Computer Science and Engineering, Texas A&M University. · Dept. of Artificial Intelligence, Sogang University. · Dept. of Electronic Engineering, Sogang University.
A Capability-Aware Backup-Recoverability Filter for Heterogeneous Multi-Robot Navigation
Oct 30, 2026Joonkyung Kim, Yanze Zhang, Wenhao Luo +1Multi-Robot Navigation in Unknown Environments Safe Robot Navigation
Department of Computer Science and Engineering, Texas A&M University · Department of Computer Science, University of Illinois Chicago
Learning Multi-Agent Task Assignment and Navigation in the Factory: from Simulation to Real Robots
Sep 13, 2026Abdalwhab Bakheet Mohamed Abdalwhab, Giovanni Beltrame, David St-OngeMulti-Robot Navigation in Unknown Environments Decentralized MARL
INIT Robots Lab, École de technologie supérieure, 1100 Notre-Dame W., Canada · MISTLab, Department of Computer and Software Engineering, Polytechnique Montréal, Canada
Mobile Multi-Robot Navigation under Runtime Uncertainty via Koopman Operator Learning and Nonlinear Model Predictive Control
Sep 12, 2026Xiaobin Zhang, Konstantinos KarydisMulti-Robot Navigation in Unknown Environments Robot Navigation
University of California, Riverside, Riverside CA 92551, USA
Dec-MARVEL: Decentralized Multi-Agent Exploration without Communication under Budget Constraints
Jul 10, 2026Janghyun Cho, Jimmy Chiun, Guillaume Sartoretti +1Multi-Robot Coordination Multi-Robot Exploration
Dept. of Artificial Intelligence, Sogang University. · Dept. of Mechanical Engineering, College of Design and Engineering, National University of Singapore. · Dept. of Electronic Engineering, Sogang University.
SPACE: Swarm Pheromone Fields for Adaptive Collision-Aware Exploration
Jun 28, 2026Haohua Que, Haojia Gao, Mingkai Liu +3Robot Collision Avoidance Swarm Robotics
Department of Electronic Engineering, Tsinghua University, Beijing, China. · Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, China. · School of Software and Microelectronics, Peking University, Beijing, China.
Collaborative Navigation and Exploration with $β$ -Sparse Gaussian Processes
May 25, 2026Evangelos Psomiadis, Dipankar Maity, Panagiotis TsiotrasMulti-Robot Systems Robot Navigation
D. Guggenheim School of Aerospace Engineering, Georgia Tech, Atlanta, GA, USA · Department of Electrical and Computer Engineering, UNC Charlotte, Charlotte, NC, USA
Flying Together: Human-Guided Immersive Shared Control for Aerial Robot Teams in Unknown Environments
May 20, 2026Lou De Bel-Air, Luca Morando, Ruitao Chen +7Multi-Robot Motion Planning Aerial Robotics
New York University, NY 10012, USA · Ecole Polytechnique Federale de Lausanne, Station 9 CH-1015 Lausanne, Switzerland · University of California Berkeley, Department of Electrical Engineering and Computer Sciences, Berkeley, CA 94720, USA
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
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
PRoID: Predicted Rate of Information Delivery in Multi-Robot Exploration and Relaying
Apr 12, 2026Seungchan Kim, Seungjae Baek, Micah Corah +3Multi-Robot Exploration Multi-Robot Coordination
Carnegie Mellon University Robotics Institute · Ulsan National Institute of Science & Technology · Colorado School of Mines +2
Can a Robot Walk the Robotic Dog: Triple-Zero Collaborative Navigation for Heterogeneous Multi-Agent Systems
Mar 23, 2026Yaxuan Wang, Yifan Xiang, Ke Li +5Multi-Robot Navigation in Unknown Environments Robot Navigation
Yuanpei College, Peking University · School of Computer Science, Peking University · School of Computer Science, Beijing University of Posts and Telecommunications +2
Perception-Aware Communication-Free Multi-UAV Coordination in the Wild
Mar 9, 2026Manuel Boldrer, Michal Kamler, Afzal Ahmad +1Multi-Robot Coordination Multi-Robot Navigation in Unknown Environments
Department of Cybernetics, Czech Technical University in Prague, Karlovo namesti 13, 121 35 Prague 2, Czechia.
VORL-EXPLORE: A Hybrid Learning Planning Approach to Multi-Robot Exploration in Dynamic Environments
Mar 9, 2026Ning Liu, Sen Shen, Zheng Li +4Multi-Robot Exploration Multi-Robot Motion Planning
The University of Western Australia · The Chinese University of Hong Kong · Karlsruhe Institute of Technology +1
Decentralized and Fully Onboard: Range-Aided Cooperative Localization and Navigation on Micro Aerial Vehicles
Feb 18, 2026Abhishek Goudar, Angela P. SchoelligMulti-Robot Navigation in Unknown Environments Cooperative Localization
The authors are with the Learning Systems and Robotics Lab at the Technical University of Munich, Germany, and the University of Toronto Institute for Aerospace Studies, Canada. They are also affiliated with the University of Toronto Robotics Institute, the Munich Institute of Robotics and Machine Intelligence (MIRMI), and the Vector Institute for Artificial Intelligence.

Oct 30, 2026J/K move · Enter open · S save

Capability-Conditioned Graph Control Barrier Functions for Zero-Shot Safe Navigation of Heterogeneous Mobile Robot Teams

Joonkyung Kim, Janghyun Cho, Jeehyun Lee, Changjoo Nam+1

Dept. of Computer Science and Engineering, Texas A&M University. · Dept. of Artificial Intelligence, Sogang University. · Dept. of Electronic Engineering, Sogang University.

Multi-Robot Navigation in Unknown Environments Multi-Robot Systems Control Barrier Functions Robot Safety Multi-Robot Coordination Zero-Shot Coordination

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Multi-robot systems are increasingly deployed as heterogeneous fleets with diverse kinematic and actuation capabilities. While graph control barrier function (GCBF) methods provide a scalable framework for decentralized safe control, existing approaches typically assume homogeneous robot dynamics. Methods that directly encode robot classes can distinguish known types, but do not represent state-dependent motion capabilities or naturally transfer to unseen robot models. To address this challenge, we propose the Capability-Conditioned Heterogeneous Graph Control Barrier Function (CC-HGCBF), defined in a shared second-order reference-point operational space. This formulation provides a common geometric representation of safety across heterogeneous robots while retaining their model-specific dynamics and admissible control constraints. To enable zero-shot transfer, we introduce the Radial Capability Field (RCF), a compact, fixed-dimensional representation of each robot's state-dependent finite-horizon reachable velocity set. Conditioning the shared graph barrier and decentralized policy on the RCF enables them to adapt to changes in robot state, kinematic constraints, and control limits without relying on predefined robot identities. We jointly train the barrier and policy using proactive safety labeling and neural CBF-QP supervision, and evaluate them on mixed teams containing both seen and unseen robot models. Experiments demonstrate scalable safe coordination and zero-shot transfer to robot models and capability variations withheld during training. Physical-robot experiments further demonstrate zero-shot deployment to unseen kinematic models without retraining.