Multiple Mobile Robot System Research Articles

Advancements in Cooperative Mobile Robots Control Strategies for Large-Scale Material Transport

This paper explores groundbreaking advancements in control strategies for cooperative mobile robots used in large-scale material transport, a critical aspect of modern industrial, manufacturing, logistics, and construction sectors. It delves into the development of sophisticated systems that enable seamless coordination among multiple mobile robot systems. The research presents a novel hierarchical finite state automaton for dynamic mission adaptation and a null space-based control scheme for precise task execution and enhanced system resilience. The introduction of Mecanum wheels facilitates flexible movement and manipulation of materials, thereby increasing operational efficiency and safety. Cutting-edge sensory technology, including LiDAR, and the implementation of the Robot Operating System are highlighted for their roles in enhancing autonomous navigation and intelligent operation. Additionally, the paper discusses the impact of centralized and decentralized control methods in ensuring safe, cooperative object transport. The findings contribute to the vision of Industry 4.0 by promoting the integration of automation and robotic cooperation in complex environments and present a foundational blueprint for further research. Challenges for future work such as scalability, communication efficiency, collision avoidance, and energy efficiency are also considered, underscoring the need for ongoing development of robust and scalable robotic systems to address modern transport challenges.

Adaptive region tracking control for multiple nonholonomic mobile robot systems subject to collision avoidance

Adaptive region tracking control for multiple nonholonomic mobile robot systems subject to collision avoidance

Collision Avoidance and Give Way of Heterogeneous and Variable-Sized Multiple Mobile Robots Based on Glued Nodes

Multiple mobile robot systems (MMRSs) play an important role in workshops, storage and other scenarios. A complex MMRS can contain heterogeneous robots, and even the robot sizes are not fixed, making it more difficult to avoid collisions. As a widely studied method, the zone-controlled method is not accurate enough for a system with heterogeneous and variable-sized robots, and it increases the difficulty of applying MMRS. Based on the concept of glued nodes, this paper proposes a more accurate calculation method than the zone-controlled method to avoid collisions among heterogeneous and variable-sized robots. In order to improve the efficiency of calculating glued nodes, this paper proposes a time-to-space method, which has a constant complexity after the system runs long enough. In addition to collision avoidance, this paper also studies the problem of giving way of idle robots. This paper proposes a method which can detect those idle robots blocking the working robots and plan paths for the idle robots to find avoidance nodes to give way to the working robots. Simulation experiments are carried out based on a real automated production line scenario, and the experimental results prove the effectiveness and efficiency of the proposed methods. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In a complex MMRS, the size of different robots can be different, and even the size of a robot is different when loaded and unloaded. One of the motivations of this paper is to avoid collisions in such a complex MMRS. A collision avoidance method is proposed to avoid collisions among robots by allocating nodes in real time. At the same time, this paper also addresses the problem of idle robots blocking working robots. If an idle robot blocks some working robots, an avoidance node will be found for the idle robot to give way to the working robots. The methods proposed in this paper can be applied to the roadmap of any structure. This means that in a scenario, regardless of the structure of roadmap and the different sizes of robots, the methods can be applied directly. The methods have been applied to many practical industrial projects in warehousing, manufacturing and other scenarios, and greatly reduces the difficulty of applying MMRS. In future research, there is a need to improve the efficiency of the methods so that they can be applied to a large-scale system.

Distributed finite-time formation control of multiple mobile robot systems without global information

Distributed finite-time formation control of multiple mobile robot systems without global information

Multi-level control for multiple mobile robot systems

This paper contributes with a multi-level, hierarchical control system for a fleet of mobile robots sharing a common 2D motion space. The system consists of three levels, with the top level being a supervisor based on a discrete representation of the Multiple Mobile Robot System (MMRS), in which robot motion processes are seen as sequences of stages. The supervisor controls centrally the changes of their stages by robots, ensuring their collision-, and deadlock-free concurrent movement. The intermediate control level supervises locally the execution of robot motion on individual stages in a manner consistent with the decisions of the top level. The lowest level, robot control, is responsible for motion execution as determined by the local supervisor. We capitalize on some earlier results concerning the supervisory control of MMRS and propose a common framework for three supervisory control models. Then we propose relevant solutions for the local supervisors, in particular, a DES-based robot-motion-mode control and application of the Artificial Potential Field model for ensuring collision-free motion of two robots sharing a space sector. Next we assume simple robot control and subject the system to simulation experiments aimed at comparing the impact of the different solutions on the performance of MMRS.

A Study of the Global Topological Map Construction Algorithm Based on Grid Map Representation for Multirobot

In some large environments where humans and machines coexist, such as smart factories, restaurants, and hotels, multiple mobile robots system have certain advantages over single mobile robot in terms of task complexity, execution efficiency, and system robustness. However, path conflicts and blockages may occur among robots without effective global coordination method, especially in some special areas like narrow straight roads (N-S-R) and crossroads (C-R). To solve this problem, using the global topology map might be a good solution. Therefore, this paper proposes a method called Surplus Topology Generation Algorithm (<i>STGA</i>) for constructing a global topological map based on grid map representation. On the basis of grid maps, we designed <i>Node-Filter</i> to generate enough topological nodes, and simplified the node set by <i>Node-Selection</i>. In special areas such as N-S-R and C-R, which are prone to path conflicts and blocking scenarios, we extracted the Harris corner point and combined them to select the corner point combinations that characterize some special features like passage entrance, etc. Then, feature nodes that can characterize the special features were obtained by establishing mapping relationships between nodes and corner point combinations. Finally, the global topology map was obtained after establishing the reachability relationships between nodes. The simulation experiment results showed that the topological maps generated by <i>STGA</i> had obvious advantages in the richness of topological relationships. Besides, the topological maps also showed certain advantages compared to grid maps for the planning efficiency and security of global paths. Furthermore, the rich topological nodes on the global topological map were feasible in solving path conflicts of multiple robots. <i>Note to Practitioners</i>&#x2014;Multi-robot system has better efficiency and system robustness, but how to solve the path conflicts among robots is a problem. We propose a method to solve multi-robot conflicts with global topological maps. This topological map is constructed by STGA. The grid map environment is discretized into a set of topological nodes, which have been used to maintain the spatial transitions of each robot in the environment. When robots encounter unavoidable path conflicts, they are scheduled with the help of topological nodes to achieve orderly and efficient collaboration.

Hybrid motion control for multiple mobile robot systems

Hybrid motion control for multiple mobile robot systems

An Algorithm for Task Allocation and Planning for a Heterogeneous Multi-Robot System to Minimize the Last Task Completion Time.

This paper proposes an algorithm that provides operational strategies for multiple heterogeneous mobile robot systems utilized in many real-world applications, such as deliveries, surveillance, search and rescue, monitoring, and transportation. Specifically, the authors focus on developing an algorithm that solves a min–max multiple depot heterogeneous asymmetric traveling salesperson problem (MDHATSP). The algorithm is designed based on a primal–dual technique to operate given multiple heterogeneous robots located at distinctive depots by finding a tour for each robot such that all the given targets are visited by at least one robot while minimizing the last task completion time. Building on existing work, the newly developed algorithm can solve more generalized problems, including asymmetric cost problems with a min–max objective. Though producing optimal solutions requires high computational loads, the authors aim to find reasonable sub-optimal solutions within a short computation time. The algorithm was repeatedly tested in a simulation with varying problem sizes to verify its effectiveness. The computational results show that the algorithm can produce reliable solutions to apply in real-time operations within a reasonable time.

Distributed leader-following formation control for multiple nonholonomic mobile robots via bioinspired neurodynamic approach

This paper investigates the distributed leader-following formation control problem for multiple nonholonomic wheeled mobile robots via a bioinspired neurodynamic approach. To do this, first, we develop a distributed estimator for each follower robot which uses its own information and the information of its neighboring robots to estimate the leader’s states. Second, a formation tracking control law is proposed for each follower robot based on the estimated states of the leader using the backstepping technique. Then, a bioinspired neurodynamics-based backstepping controller is designed to solve the impractical velocity jumps problem. Furthermore, Lyapunov function-based approach is utilized to derive sufficient conditions which guarantee asymptotic stability of the multiple mobile robot system. Finally, simulation results are presented to illustrate the effectiveness of the proposed controllers.

Multi-level control for mobile robot systems *

The paper contributes with a hybrid controller for multiple mobile robot systems (MMRS) that ensures the correct accomplishment of its mission by each robot. We capitalize on earlier results concerning the supervision of the robot flow, in particular the concept of partitioning the motion area into cells. Then the system comprises three control levels: DES (Discrete Event System) based cell-transition controller, APF (Artificial Potential Field) based cell-traverse controller, and CTS (Continuous Time System) based robot motion controller. The breakdown of the coordination concept into two control levels allows the optimal solution of the system liveness problem, and the holistic approach to the control of MMRS provides for its direct implementation in both a simulator and a real-robot test-bed.

Time-Optimal Velocity Tracking Control for Consensus Formation of Multiple Nonholonomic Mobile Robots.

The problem of velocity tracking is considered essential in the consensus of multi-wheeled mobile robot systems to minimise the total operating time and enhance the system’s energy efficiency. This study presents a novel switched-system approach, consisting of bang-bang control and consensus formation algorithms, to address the problem of time-optimal velocity tracking of multiple wheeled mobile robots with nonholonomic constraints. This effort aims to achieve the desired velocity formation in the least time for any initial velocity conditions in a multiple mobile robot system. The main findings of this study are as follows: (i) by deriving the equation of motion along the specified path, the motor’s extremal conditions for a time-optimal trajectory are introduced; (ii) utilising a general consensus formation algorithm, the desired velocity formation is achieved; (iii) applying the Pontryagin Maximum Principle, the new switching formation matrix of weights is obtained. Using this new switching matrix of weights guarantees that at least one of the system’s motors, of either the followers or the leader, reaches its maximum or minimum value by using extremals, which enables the multi-robot system to reach the velocity formation in the least time. The proposed approach is verified in a theoretical analysis along with the numerical simulation process. The simulation results demonstrated that using the proposed switched system, the time-optimal consensus algorithm behaved very well in the networks with different numbers of robots and different topology conditions. The required time for the consensus formation is dramatically reduced, which is very promising. The findings of this work could be extended to and beneficial for any multi-wheeled mobile robot system.

Fixed-time formation tracking for multiple nonholonomic wheeled mobile robots based on distributed observer

This paper studies the distributed fixed-time formation tracking problem of multiple nonholonomic wheeled mobile robots system over directed fixed and switching topologies. Through a classical nonlinear transformation, the formation control problem is transformed into a consensus problem. New control protocols based on a distributed observer are proposed. The directed communication topology between multiple nonholonomic wheeled mobile robots is considered. Some sufficient conditions of multiple robots achieving the desired formation shape are given. All follower robots can form the desired formation shape within a fixed settling time and make the leader in the geometric center of the formation. By adopting graph theory and fixed-time stability theory, an upper bound of settling time that is independent of the system’s initial states is obtained. Finally, two examples are presented to illustrate the correctness of the main results.

Control synthesis for multiple mobile robot systems

This work continues our study on the control synthesis for multiple mobile robot systems (MMRS). We assume a hybrid approach that comprises the supervisory control level, based on a discrete event model of MMRS, and the robot control level, based on a continuous time model of the robot motion. Our objective is to further develop the control concept towards its implementation in a real-world application – a testbed for a fleet of six laboratory robots. In the first part of the paper, we develop a methodology of the supervisory control synthesis, that employs the Petri net formalism and formally ensures the required logics of MMRS operation, as well as propose a relevant architecture of the supervisor. The second part is focused on the low-level robot control and control procedures enabling modification of the robot motion according to the supervisor’s decisions. A simulation case is presented that illustrates the operation of the system.

Anomaly Resilient Relative Pose Estimation for Multiple Nonholonomic Mobile Robot Systems

This article addresses the resilient relative pose estimation problem for multiple mobile robot systems against abnormal sensor measurements. Motivated by the fact that in real implementations, sensors used for neighboring robot detection, such as stereo camera, laser range finder, etc., may suffer from unpredictable anomalies, a resilient relative pose estimation approach is proposed such that each robot can obtain satisfactory relative pose estimates of its neighbors for further coordination algorithm design. In the proposed approach, the optimal Kalman estimate is decomposed as a weighted sum of local state estimates, based on which a convex optimization problem is formulated to generate the resilient estimation. Unlike most of the existing approaches investigating similar problems, which assume that the statistics or the bound of anomalies is known in advance, our proposed approach is not limited by this assumption. The effectiveness of the proposed method has been validated by numerical simulations and real robot experiments. It has been demonstrated that the proposed approach is comparable to the Kalman filter in the absence of sensor anomalies, while boundedness of the relative pose estimation error can be guaranteed under abnormal observations.

Cooperative Localization Algorithm Based on Hybrid Topology Architecture for Multiple Mobile Robot System

With the development of robotics, the multiple mobile robot system (MMRS) has been an attention-getting subject in recent years and has been widely used in military, civilian and other fields. Cooperative localization is the key technology of the MMRS. And observability analysis for MMRS and nonlinear problem are the foremost problems to cooperative localization. In order to enhance the accuracy of cooperative localization for MMRS, a novel cooperative localization algorithm based on hybrid topology architecture under the framework of extended Kalman filter (EKF) is proposed in this paper. In this novel algorithm, a hybrid topology architecture based on the relative position measurement graph method is adopted to enhance the usage efficiency of observations, improving the cooperative localization accuracy. Meanwhile, EKF is used in this novel cooperative localization algorithm to solve the nonlinearity of the MMRS. Finally, a real dataset is used to verify the availability and superiority of this novel algorithm.

Application of probability to enhance the performance of fuzzy based mobile robot navigation

This paper presents a new path planning algorithm based on Probability and Fuzzy Logic (PFL) as a duality technique to enhance the performance of Fuzzy Logic alone. Fuzzy Logic interacts with the grading of obstacles existed in the path and probability lies over the decision to move the mobile robot. The fuzzy grading correspondence with the probabilistic decision is the primary function of moving the mobile robot towards the goal and the secondary is path planning which lies over the probability distribution function. The distance–speed combination rule is developed for effective navigation. The single and multiple mobile robot systems have been tested successfully in a dense environment in presence of obstacles (static and dynamic) and moving goal. The obtained results are optimal when compared to other navigational approaches in sense of navigational path length and time in the static and dynamic environment.

Practical time‐varying formation tracking for multiple non‐holonomic mobile robot systems based on the distributed extended state observers

Practical time-varying formation tracking analysis and design problems for multiple non-holonomic mobile robot systems with directed interaction topologies are investigated by using the distributed extended state observers, where the practical time-varying formation tracking error is controlled within an arbitrary small bound. Different from the previous work, the dynamics of each robot is non-holonomic and the followers are required to form the practical time-varying formation with respect to the leader of unknown control inputs. Besides, the disturbances and the uncertainties are considered in the dynamic model of the follower. Distributed extended state observers are constructed by using only the neighbouring relative information to estimate both the state and the unknown control inputs of the leader simultaneously. A practical time-varying formation tracking protocol is presented based on the distributed extended state observers. The gain matrices of the observers in the practical time-varying formation tracking protocol can be obtained by solving three linear matrix inequalities. Moreover, the stability of the multiple non-holonomic mobile robot system under the proposed protocol is proved by using the properties of the Laplacian matrix and the Lyapunov stability theory. Finally, two numerical simulation examples are given to illustrate the effectiveness of the obtained theoretical results.

Cooperative Localization Algorithm for Multiple Mobile Robot System in Indoor Environment Based on Variance Component Estimation

The Multiple Mobile Robot (MMR) cooperative system is becoming a focus of study in various fields due to its advantages, such as high efficiency and good fault tolerance. However, the uncertainty and nonlinearity problems severely limit the cooperative localization accuracy of the MMR system. Thus, to solve the problems mentioned above, this manuscript presents a cooperative localization algorithm for MMR systems based on Cubature Kalman Filter (CKF) and adaptive Variance Component Estimation (VCE) methods. In this novel algorithm, a nonlinear filter named CKF is used to enhance the cooperative localization accuracy and reduce the computational load. On the other hand, the adaptive VCE method is introduced to eliminate the effects of unknown system noise. Furthermore, the performance of the proposed algorithm is compared with that of the cooperative localization algorithm based on normal CKF by utilizing the real experiment data. In addition, the results demonstrate that the proposed algorithm outperforms the CKF cooperative localization algorithm both in accuracy and consistency.

Object Conveyance Algorithm for Multiple Mobile Robots based on Object Shape and Size

This paper describes a determination method of a number of a team for multiple mobile robot object conveyance. The number of robot on multiple mobile robot systems is the factor of complexity on robots formation and motion control. In our previous research, we verified the use of the complex-valued neural network for controlling multiple mobile robots in object conveyance problem. Though it is a significant issue to develop effective determination team member for multiple mobile robot object conveyance, few studies have been done on it. Therefore, we propose an algorithm for determining the number of the team member on multiple mobile robot object conveyance with grasping push. The team member is determined based on object weight to obtain appropriate formation. First, the object shape and size measurement is carried out by a surveyor robot that approaches and surrounds the object. During surrounding the object, the surveyor robot measures its distance to the object and records for estimating the object shape and size. Since the object shape and size are estimated, the surveyor robot makes initial push position on the estimated push point and calls additional robots for cooperative push. The algorithm is validated in several computer simulations with varying object shape and size. As a result, the proposed algorithm is promising for minimizing the number of the robot on multiple mobile robot object conveyance.

Fuzzy Logic Based Navigation for Multiple Mobile Robots in Indoor Environments

The work presented in this paper deals with a navigation problem for multiple mobile robot system in unknown indoor environments. The environment is completely unknown for all the robots and the surrounding information should be detected by the proximity sensors installed on the robots’ bodies. In order to guide all the robots to move along collision-free paths and reach the goal positions, a navigation method based on the combination of a set of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensors’ data is used for avoiding small convex obstacles or moving objects which include both dynamic obstacles and other robots. For big convex obstacles or concave ones, a wall following strategy is designed for dealing with these special situations. In this paper, a state memorizing strategy is also proposed for the “infinite repetition” or “dead cycle” situations. Finally, when there is no collision risk, the robots will be guided towards the targets according to a target positioning strategy. Most of these strategies are achieved by the means of fuzzy logic controllers and uniformly applied for every robot. The simulation experiments verified that the proposed method has a positive effectiveness for the navigation problem.