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formation control of networked mobile robots with weighted directed topology using the Udwadia-Kalaba approach

NONLINEAR DYNAMICS 2025年第6期113卷 5423-5438页

作者： Kang, Yijie Hao, Yuqing Wang, Qingyun Chen, Guanrong Beihang Univ Sch Aeronaut Sci & Engn Beijing Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

In this paper, the formation control of networked mobile robots is investigated by using the Udwadia-Kalaba approach. The communication topology is directed, weighted and has a spanning tree. By reformulating the control objective as a constrained equation, a formation controller is designed for the leaderless case. Moreover, the trajectories of the formation are rigorously analyzed. It is derived that there are three typical geometric patterns: a point, a straight line and a circle. Further, to satisfy requirements on the formation trajectories in practical applications, a formation controller is designed for the leader-following case. Finally, some numerical simulations are provided to illustrate the effectiveness of the proposed controllers.

关键词： formation control Trajectory analysis Weighted directed topology Udwadia-Kalaba approach

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formation control in Agents' Local Coordinate Frames for Arbitrary Initial Attitudes

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2025年第1期12卷 993-1005页

作者： Garanayak, Chinmay Mukherjee, Dwaipayan Indian Inst Technol Dept Elect Engn Mumbai 400076 India Indian Inst Technol Elect Engn Mumbai 400076 India

In this article, we address formation tracking control in agents' body coordinate frames while imposing no assumptions, such as positive definiteness on agents' initial attitude matrix. Difficulty in achieving formation control is exacerbated when agents are unable to access their absolute attitudes relative to a common frame of reference, and initial attitude matrices are required to be restricted to special sets. Addressing this issue, we present a distributed fixed-time attitude synchronization law, which utilizes only relative attitude measurements to align the agents' coordinate frames almost globally in finite time and locally in fixed time. The proposed law ensures the global asymptotic convergence of formation tracking error for displacement-based formation control in a leader-follower topology. We also establish global uniformly asymptotic stability for bearing-only formation tracking. A Lyapunov-based attitude estimation algorithm is proposed to estimate the attitudes up to a common reference frame in finite time without using Gram-Schmidt orthogonalization. For nonholonomic agents, formation stabilization in agents' local coordinate frame is studied using these attitude estimates and bearing-only measurements. Finally, to illustrate the applicability of our results, simulations are presented.

关键词： formation control Attitude control Displacement measurement Convergence Synchronization Estimation Vectors Attitude estimation and synchronization bearing-only measurements formation control

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formation control and path planning of multi-robot systems via large language models

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Science China(Information Sciences) 2025年第5期68卷 72-88页

作者： Dong XUE Xuanjie ZHOU Ming WANG Fangzhou LIU Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology Research Institute of Intelligent Control and Systems School of Astronautics Harbin Institute of Technology

Existing path planning and coordination control methods for multi-robot systems(MRS) typically rely on predefined rules and rudimentary algorithms. However, these methods often struggle to adapt flexibly to complex environments and to adjust motion targets appropriately. To address this challenge, this study presents a large language model(LLM)-assisted framework. By integrating textual descriptions of complex motion constraints, robot information, and local environmental data as inputs, LLMs generate motion objectives and translate them into executable control commands for the robots, thereby achieving coordinated control and path planning. This framework facilitates the generation, maintenance, and reshaping of formations in MRSs during path planning, applicable to both obstacle-free and obstacle-avoidance environments. Simulation results demonstrate that LLM-based control strategies enhance the autonomy, adaptability, flexibility, and robustness of MRS by processing complex information, making intelligent decisions, adapting to environmental changes, and handling disturbances and uncertainties.

关键词： multi-robot systems formation control path planning obstacle avoidance large language models

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formation control of high-order linear discrete-time multiple unmanned aerial vehicles systems in noisy environments

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2025年第2期56卷 335-346页

作者： Wang, Zi-Xuan Zong, Xiaofeng Wang, Mingyu Gai, Ling-Jie China Univ Geosci Sch Automat Wuhan 430074 Peoples R China Hubei Key Lab Adv Control & Intelligent Automat Co Wuhan Peoples R China Minist Educ Engn Res Ctr Intelligent Technol Geoexplorat Wuhan Peoples R China

formation control of high-order linear discrete-time multiple unmanned aerial vehicles (multi-UAVs) systems with multiplicative noises is studied in this article. Because of the existence of multiplicative noises, classical methods for discrete-time system control problems should be improved. Here, we develop a new discrete-time formation protocol for multi-UAVs systems. The stochastic Lyapunov stability theory and the positive definiteness theory of a generalized algebraic Riccati equation are then used to derive sufficient conditions for formation feasibility.

关键词： formation control multi-UAVs systems multiplicative noises high-order linear system

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formation control of Unmanned Helicopters Moving Target Tracking Obstacle Avoidance and Maintenance Connectivity

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INTERNATIONAL JOURNAL OF ENGINEERING 2025年第9期38卷 2072-2084页

作者： Ghaderi, F. Toloei, A. Shahid Beheshti Univ Dept New Technol & Aerosp Engn Tehran Iran

This research addresses the control of unmanned helicopters, emphasizing formation control, target tracking, obstacle avoidance, and continuity maintenance. The study employs Terminal Sliding Mode control (TSMC) to regulate the helicopters' position and attitude, while a Generalized Predictive control (GPC) strategy is utilized for formation control through a leader-follower approach. Obstacle avoidance is achieved using an Artificial Potential Field (APF) method. Simulation results indicate rapid convergence times of less than three seconds across six distinct missions, demonstrating the capability of the helicopters to navigate both static and dynamic obstacles while maintaining their formation. The initial three missions involve three helicopters organized in a triangular formation, successfully avoiding obstacles and maintaining continuity with an error rate below 1%. The subsequent three missions, involving five helicopters in a pentagonal configuration, similarly illustrate effective navigation and dynamic target tracking. Notably, the leader helicopter consistently tracks both static and dynamic targets, ensuring the integrity of the formation. This study contributes to the field by exploring the complexities of multi-agent helicopter operations and obstacle traversal, highlighting the critical importance of maintaining connectivity and formation during dynamic scenarios. The findings underscore the effectiveness of the proposed control strategies, offering valuable insights for future applications in various sectors, including military and civilian domains.

关键词： Unmanned Helicopter Obstacle Avoidance formation control Sliding Mode control

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Efficient Path Planning and formation control in Multi-Robot Systems: A Neural Fields and Auto-Switching Mechanism Approach

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IEEE ACCESS 2025年 13卷 8270-8285页

作者： Fareh, Raouf Baziyad, Mohammed Rabie, Tamer Farouk Khadraoui, Sofiane Rahman, Mohammad Habibur Univ Sharjah Elect Engn Dept Sharjah U Arab Emirates Univ Sharjah RISE Sharjah U Arab Emirates Univ Sharjah Comp Engn Dept Sharjah U Arab Emirates Univ Wisconsin Milwaukee Mech Engn Dept Milwaukee WI 53211 USA

Current implementations of leader-follower systems in multi-robot environments typically separate path planning and formation control, often leading to inefficiencies in execution speed, path quality, and system stability. These systems rely on complex control strategies that struggle to adapt to dynamic and challenging environments, resulting in sub-optimal performance and potential collisions. This paper presents a novel approach to enhancing the path planning and formation control of multi-robot leader-follower systems by integrating neural fields and novel potential field modeling. The primary focus is on developing a unified platform that addresses the challenges of maintaining formation integrity, optimizing path quality, and ensuring real-time responsiveness. Neural Fields, which has gained significant traction in the past few years, utilizes fully connected neural networks to effectively encode continuous signals across various dimensions and resolutions. This growing interest in neural fields has highlighted their potential to provide solutions that are not only more precise and high-fidelity but also highly expressive and efficient in terms of memory usage. Thus, this work proposes leveraging neural fields to achieve high-quality path planning in significantly reduced time. By utilizing the expressiveness and memory efficiency of neural fields, the suggested approach aims to generate optimized paths quickly, making it well-suited for real-time applications where both accuracy and speed are critical. On the other hand, the follower robots are equipped with an auto-switching potential method, which intelligently toggles between attractive forces guiding the followers toward the leader and repulsive forces preventing collisions based on a mathematical model. The effectiveness of this approach is validated through experiments, demonstrating significant improvements in execution speed, path smoothness, and overall system stability compared to competitive method

关键词： Robots Robot kinematics Path planning Mathematical models control systems Mobile robots Heuristic algorithms Neural networks Multi-robot systems formation control Multi-robot leader-follower path planning potential field kinematic control

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Self-Triggered formation control of Heterogeneous Quadrotors on TSE(3)^N in Presence of External Disturbances

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2025年

作者： Sharma, Manmohan Ramalingam, Sakthivel Vellore Inst Technol Sch Elect Engn Chennai India Vellore Inst Technol Sch Comp Sci & Engn Chennai India

In this paper, the formation control strategy is designed for a class of multi-agent systems with heterogeneous quadrotor UAVs structure subjected to external disturbances and modeling uncertainties. Specifically, a self-triggered scheme is developed to reduce network load, which computes the next triggering instant based on past and current transmitted states. Further, the unmeasurable states are estimated by applying an extended state observer. Based on the LaSalle's invariance principle, Lyapunov-based approach is analyzed with some sufficient conditions proposed for the considered heterogeneous systems, while avoiding the Zeno phenomenon. Finally, we validate the effectiveness of the proposed algorithms through a simulation result.

关键词： extended state observer formation control multi-agent systems quadrotors self-triggered control

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Employing Fuzzy Adaptive and Event-Triggered Approaches to Achieve formation control of Nonholonomic Mobile Robots Under Complete State Constraints

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APPLIED SCIENCES-BASEL 2025年第5期15卷

作者： Wang, Kai Lu, Jinnan Zhou, Haodong Liaoning Univ Technol Elect Engn Coll Jinzhou 121001 Peoples R China Liaoning Univ Engn & Technol Fac Mech & Engn Fuxin 123000 Peoples R China Dalian Maritime Univ Nav Coll Dalian 116026 Peoples R China

This article delves into the problem of fuzzy adaptive event-triggered (ET) formation control for nonholonomic mobile robots (NMRs) subject to full-state constraints. Fuzzy logic systems (FLSs) are employed to identify the unknown nonlinear functions within the system. To guarantee that all system states remain within their constraint boundaries, barrier Lyapunov functions (BLFs) are meticulously constructed. Subsequently, within the framework of the backstepping control design algorithm, we propose a novel fuzzy adaptive ET formation controller. Our ET mechanism can achieve an overall resource-saving rate of 88.17% for the four robots. Rigorous theoretical analysis demonstrates that the designed strategy not only ensures the stability of the controlled NMRs but also enables the formation tracking errors to converge to a small neighborhood around zero. Notably, the BLFs-based control approach presented herein endows the system with the capacity to avoid collisions to a certain degree, enhancing the overall safety and reliability of the robot formation. Finally, a simulation example is provided. The results vividly illustrate the effectiveness and practicality of the proposed theory, validating its potential for real-world applications in the field of nonholonomic mobile robot formation control.

关键词： barrier Lyapunov function backstepping control design formation control full-state constraints nonholonomic mobile robot systems

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Safe formation control of Uncertain Multiagent Systems From a Bayesian Perspective

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IEEE TRANSACTIONS ON AUTOMATIC control 2025年第3期70卷 1929-1934页

作者： Li, Boqian Guo, Zhenyuan Hu, Cheng Zhu, Song Wen, Shiping Univ Technol Sydney Fac Engn & Informat Technol Australian AI Inst Sydney NSW 2007 Australia Hunan Univ Coll Math & Econometr Changsha 410082 Peoples R China Xinjiang Univ Coll Math & Syst Sci Urumqi 830017 Peoples R China China Univ Min & Technol Sch Math Xuzhou 221116 Peoples R China

In this study, we address the formation control of uncertain multiagent systems with a safety requirement of collision avoidance. The control inputs are determined through quadratic programming (QP) solvers, where both the control Lyapunov function condition and control barrier function condition serve as constraints in the QP problem to achieve the control and safety objectives, respectively. In this work, the Bayesian theorem plays a crucial role in two key aspects. First, the unknown uncertainties are estimated using Gaussian process models, which provide mean and variance information incorporated into the QP framework to determine the control inputs. The integration ensures the attainment of desired objectives with high probability. Second, the Bayesian optimization algorithm is employed to optimize some hyperparameters. These selected hyperparameters enhance the solvability of the QP problem and simultaneously improve the control performance of multiagent systems.

关键词： Safety formation control Vectors Bayes methods Uncertainty Optimization Multi-agent systems Gaussian processes Collision avoidance Aerospace electronics Bayesian optimization (BO) control barrier function control Lyapunov function (CLF) Gaussian process (GP)

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Distributed Model Predictive Cross-Dimensional formation control for Heterogeneous Multiagent Systems

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IEEE ACCESS 2025年 13卷 61549-61563页

作者： Liu, Haitao Li, Zhaoxin Mai, Qingqun Liu, Haochun Tian, Xuehong Guangdong Ocean Univ Sch Mech Engn Zhanjiang 524088 Peoples R China Guangdong Ocean Univ Shenzhen Inst Shenzhen 518120 Peoples R China Guangdong Engn Technol Res Ctr Ocean Equipment & M Guangdong Prov Key Lab Intelligent Equipment South Zhanjiang 524088 Peoples R China

In this paper, a distributed predefined-time model predictive formation control method is proposed for second-order multidimensional cross-dimensional heterogeneous multiagent systems (HMASs) with collision avoidance, switching topology and formation transformation. First, a distributed cross-dimensional formation control protocol based on the full or partial information of neighboring agents is proposed for multidimensional heterogeneous multiagent systems. Second, a formation cooperative control approach that can quickly achieve the desired formation and formation transformation is designed by combining the predefined-time control strategy with the auxiliary control law of Lyapunov-based distributed model predictive control (DMPC). In addition, collision avoidance among agents can be achieved by adding a collision penalty mechanism to the cost function. Finally, an application to heterogeneous multiagent unmanned surface vehicle and unmanned underwater vehicle (USV-UUV) systems, through which the effectiveness of the proposed results has been demonstrated, and the simulation results are analyzed to evaluate the effectiveness and reliability of the proposed method.

关键词： Multi-agent systems formation control Predictive control Vectors Protocols Predictive models Trajectory Oceans Intelligent agents Collision avoidance Heterogeneous multiagent systems USV-UUV systems distributed formation control trajectory tracking control model predictive control

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