Multi-robot Rigid Formation Navigation via Synchronous Motion and Discrete-time Communication-Control Optimization
Qun Yang, Soung Chang Liew
- Year
- 2025
- Access
- Open access
Abstract
Rigid-formation navigation of multiple robots is essential for applications such as cooperative transportation. This process involves a team of collaborative robots maintaining a predefined geometric configuration, such as a square, while in motion. For untethered collaborative motion, inter-robot communication must be conducted through a wireless network. Notably, few existing works offer a comprehensive solution for multi-robot formation navigation executable on microprocessor platforms via wireless networks, particularly for formations that must traverse complex curvilinear paths. To address this gap, we introduce a novel "hold-and-hit" communication-control framework designed to work seamlessly with the widely-used Robotic Operating System (ROS) platform. The hold-and-hit framework synchronizes robot movements in a manner robust against wireless network delays and packet loss. It operates over discrete-time communication-control cycles, making it suitable for implementation on contemporary microprocessors. Complementary to hold-and-hit, we propose an intra-cycle optimization approach that enables rigid formations to closely follow desired curvilinear paths, even under the nonholonomic movement constraints inherent to most vehicular robots. The combination of hold-and-hit and intra-cycle optimization ensures precise and reliable navigation even in challenging scenarios. Simulations in a virtual environment demonstrate the superiority of our method in maintaining a four-robot square formation along an S-shaped path, outperforming two existing approaches. Furthermore, real-world experiments validate the effectiveness of our framework: the robots maintained an inter-distance error within $\pm 0.069m$ and an inter-angular orientation error within $\pm19.15^{\circ}$ while navigating along an S-shaped path at a fixed linear velocity of $0.1 m/s$.
Keywords
Related papers
Dynamic reconfiguration in multi-robot agent systems using embedded language models
Shokhikha Amalana Murdivien, Jongsu Park, Jumyung Um
Robotics and Computer-Integrated Manufacturing · 2026
Hierarchical decision-making for UAVs’ game via LLM enhanced multi-agent reinforcement learning
Xinyu Dong, Bo Li, Guangyu Zhang +2 more
Aerospace Science and Technology · 2026
Formation optimization and obstacle avoidance decision-making methods for cooperative coverage search of multi-UUVs in underwater wreck areas
Haomiao Yu, Zeyuan Zhang, Yantian Ma
Robotics and Autonomous Systems · 2026
Human-in-the-Loop Swarms: A Bionic Swarm Approach to Real-World Soil Mapping
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu +3 more
2026