Multiple Robot System Research Articles

Decentralized fault-tolerant control of multi-mobile robot system addressing LiDAR sensor faults

The control of multi-robot formations is a crucial aspect in various applications, such as transport, surveillance and monitoring environments. Maintaining robots in a specific formation pose or performing a cooperative task is a significant challenge when a fault occurs among any of the robots. This work presents a Decentralized Fault-Tolerant Control (DFTC) scheme that addresses lidar sensor faults within a system of multiple differential wheeled mobile robots. The robots change the formation shape according to the number of available robots within the formation. A Graph theory is implemented to represent the multi-robot formation and communication. Each mobile robot is equipped with three sensors: a wheel encoder, an Inertial Measurement Unit (IMU), and a lidar sensor. Sensor fault detection and isolation (FDI) is implemented at two levels. The pose estimation obtained from the wheel encoder and IMU is fused using an extended Kalman filter (EKF), and this pose estimation is utilized at the local level of lidar sensor FDI. At the system level, the FDI of the lidar sensor involves computing a residual by comparing the pose estimation with other lidar sensors mounted on other mobile robots within the formation. The presented FTC scheme is simulated in Simulink multi-robot environments.

Predefined-time controller design for a multiple space transportation robots system based on Lp-Norm-Normalized Sign Function

This paper presents a predefined-time controller for Multiple Space transportation Robots System (MSRS), which can be applied in on-orbit assembly tasks to transport modules to pre-assembly configuration quickly. Firstly, to simplify the analysis and design of predefined-time controller, a Predefined-time Stability Criterion is proposed in the form of Composite Lyapunov Function (CLF-PSC). Besides simplicity, the CLF-PSC also has the advantage of less conservativeness due to utilization of initial state information. Secondly, a concept of Lp-Norm-Normalized Sign Function (LPNNSF) is proposed based on the CLF-PSC. Different from traditional norm-normalized sign function, the Lp-norm of LPNNSF can be selected arbitrarily according to practical control task requirements, which means that the proposed LPNNSF is more generalized and more convenient for calculation. Thirdly, a predefined-time disturbance observer and predefined-time controller are designed based on the LPNNSF. The observer has the property of predefined-time convergence to achieve quicker and more accurate estimation of the lumped disturbance. The controller has less control input and chattering phenomenon than traditional predefined-time controller. In addition, by introducing the observer into the controller, the closed-loop system enjoys high precision and strong robustness. Finally, the effectiveness of the proposed controller is verified by numerical simulations. By employing the controller, the MSRS can carry assembly modules to the desired pre-assembly configuration accurately within predefined time.

Era for multiple gynecologic surgical robotic systems in Asia market

Era for multiple gynecologic surgical robotic systems in Asia market

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.

NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment

To improve the performance of intelligent products and reasonably distribute the load of the loading robot, a multi-objective, and multi-objective (Traveling-salesman-problem, TSP) mathematical model was established. A genetic algorithm based on speed invariant and the elite algorithm is proposed to solve the multi-TSP assignment problem. To ensure the integration of the population, a population resettlement strategy with elite lakes was proposed to improve the probability of population transfer to the best Pareto solution. The experiment verified that this strategy can approach the optimal solution more closely during the population convergence process, and compared it with traditional Multi TSP algorithms and single function multi-objective Multi TSP algorithms. By comparing the total distance and maximum deviation of multiple robot systems, it is proven that this algorithm can effectively balance the path length of each robot in task allocation. From the research results, it can be seen that in genetic algorithms, resetting the population after reaching precocity can maintain the optimization characteristics of the population and have a high probability of obtaining Pareto solutions. At the same time, storing elite individuals from previous convergent populations for optimization can better obtain Pareto solutions.

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

Robotising vitreoretinal surgeries.

The use of robotic surgery in ophthalmology has been shown to offer many potential advantages to current surgical techniques. Vitreoretinal surgery requires complex manoeuvres and high precision, and this is an area that exceeds manual human dexterity in certain surgical situations. With the advent of advanced therapeutics such as subretinal gene therapy, precise delivery and minimising trauma is imperative to optimize outcomes. There are multiple robotic systems in place for ophthalmology in pre-clinical and clinical use, and the Preceyes Robotic Surgical System (Preceyes BV) has also gained the CE mark and is commercially available for use. Recent in-vivo and in-human surgeries have been performed successfully with robotics systems. This includes membrane peeling, subretinal injections of therapeutics, and retinal vein cannulation. There is huge potential to integrate robotic surgery into mainstream clinical practice. In this review, we summarize the existing systems, and clinical implementation so far, and highlight the future clinical applications for robotic surgery in vitreo-retina.

A review of coordinated multi-robot exploration

Abstract A multiple robots system provides advantages over a single robot when it comes to exploring an unfamiliar area. Due to its applications in localization and mapping, search and rescue, etc. This technology has attracted a lot of study interest. The main challenge is properly distributing target points among several robots so that they can each investigate a separate section of the environment simultaneously and ensure the shortest possible total exploration time. However, more work still needs to be done to incorporate research issues in a real setting, such as how to eliminate duplicate exploration areas by giving robots multiple target locations or how to avoid unanticipated barriers in new situations. The allocation algorithms, motion planning techniques, and exploration strategies used in multi-robot collaboration (CME) are reviewed in this paper. Additionally, it provides an explanation of the methods research teams employ to optimize traditional whale optimization algorithm (WOA), how they enhance exploration performance and speed, and a comparative analysis of these methods. We also discussed a cooperative exploration method based on dynamic Voronoi partitioning. However, we also need some obstacle avoidance algorithms to help understand the gaps and issues that will need to be solved in the upcoming years, namely how to handle unexpected impediments in unfamiliar surroundings. Lastly, a summary of potential future lines of inquiry and uses is given.

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.

Adaptive Fixed-Time Output-Feedback Optimal Time-Varying Formation Control for Multiple Omnidirectional Robot Systems

Adaptive Fixed-Time Output-Feedback Optimal Time-Varying Formation Control for Multiple Omnidirectional Robot Systems

Logistics warehousing system shelving station route planning based on X-ARM

The need for automated control in warehouse and logistics systems has increased recently, particularly in the area of cargo storage. The use of robot arms in manufacturing is an important area for development. Multi-arm actions, including switching between multiple arms, expand the number of potential operations that numerous operators can do, but they also bring more computing hurdles. Multiple robotic arm systems must operate with careful path planning. In this study, Based on previous research papers, we propose the utilization of dRRT* and mmdRRT* algorithms for efficient path planning. The dRRT* algorithm improves exploration and convergence to an ideal path by combining the advantages of the rapidly-exploring random tree (RRT) with the optimal RRT* algorithm. To address complicated and dynamic situations, the mmdRRT* algorithm, on the other hand, uses a multi-modal distribution model. We want to improve the reliability and effectiveness of path planning for various robotic arm systems by combining these two techniques.

A Deep Reinforcement Learning-Based Decentralized Hierarchical Motion Control Strategy for Multiple Amphibious Spherical Robot Systems With Tilting Thrusters

A Deep Reinforcement Learning-Based Decentralized Hierarchical Motion Control Strategy for Multiple Amphibious Spherical Robot Systems With Tilting Thrusters

Distributed Collaborative Control of Redundant Robots Under Weight-Unbalanced Directed Graphs

In consideration of the limitation of the communication and the possibility that redundant robots might deliver information at different power levels, cases under weight-unbalanced directed graphs from the network topology perspective are in larger accordance with those in multiple redundant robot systems. By moving forward along this direction, a distributed controller is proposed in this paper to handle circumstances of collaborative control of multiple redundant robots under weight-unbalanced directed graphs. This kind of control problem is modelled into generalized quadratic programming (QP) problems with equality and inequality constraints. Then, the above QP problems are solved by a proposed neural-dynamics-based method, whose stability and convergence are theoretically proved subsequently. Besides, several experimental examples are conducted, and related comparisons are provided to demonstrate the feasibility of the proposed controller.

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

Position Tracking of Multiple Robotic Manipulator Systems Associated with Communication Strength Dynamics.

In general, a multiple robotic manipulator system (MRMS) with uncertainties can be considered a composition system with a robotic manipulator subsystem (RMS) and a communication strength subsystem (CSS), and both subsystems are coupled to each other. In this paper, a new position tracking control scheme is proposed for the MRMS while considering the communication strength dynamics between robotic manipulators. The control scheme designed in this paper consists of two parts: the first part is to design the control protocol in the RMS, and the second part is to design the coupling relationship in the CSS. Through these two parts, we can achieve the position tracking of an MRMS. Firstly, the dynamical mathematical model of the RMS and CSS in the MRMS is constructed, and the corresponding assumptions are given. Then, the corresponding stability analysis is proposed, which provides the basis for a theoretical understanding of the underlying problem. Finally, an illustrative example is presented to verify the effectiveness of the proposed control scheme.

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.

Software framework concept with visual programming and digital twin for intuitive process creation with multiple robotic systems

With the progressive digitalization in industrial manufacturing, the usage of complex robotic systems in both intralogistics and production is expected to increase. This proposes a challenge for planners and shop floor workers, as programming and interacting with these various systems leads to a high cognitive load. Especially the broad range of different manufacturer specific software leads to a number of problems, e.g. the program-synchronization between different systems and the often necessary workshops for workers. These problems can lead to inefficient programming and planning operations, bad worker satisfaction and human errors. In this paper, we present a modular, system agnostic and human centered software framework that unifies the programming of different systems, to enable centralized and intuitive system programming for non-expert operators. Our software framework utilizes visual programming concepts together with an integrated digital twin of the factory and a novel graph-based programming interface. We explain our concept in detail and describe our validation through integration into a realistic industrial setup with three different systems. In addition, we provide an evaluation of our concept's usability with an experimental user study and discuss the results of the study and the software implementation. Our study results show that even non-technical users are able to use our software after a brief introduction to create complex processes that involve multiple machines working in parallel. All users reported high usability and expert users reported that the visual process editor has enough features to create processes for industrial applications. Finally, we conclude this paper by providing an outlook on future work and use-cases of our software.

Robust and Collision-Free Formation Control of Multiagent Systems With Limited Information.

This article investigates the collision-free cooperative formation control problem for second-order multiagent systems with unknown velocity, dynamics uncertainties, and limited reference information. An observer-based sliding mode control law is proposed to ensure both the convergence of the system's tracking error and the boundedness of the relative distance between each pair of agents. First, two new finite-time neural-based observer designs are introduced to estimate both the agent velocity and the system uncertainty. The sliding mode differentiator is then employed for every agent to approximate the unknown derivatives of the formation reference to further construct the limited-information-based sliding mode controller. To ensure that the system is collision-free, artificial potential fields are introduced along with a time-varying topology. An example of a multiple omnidirectional robot system is used to conduct numerical simulations, and necessary comparisons are made to justify the effectiveness of the proposed limited-information-based control scheme.

Hybrid motion control for multiple mobile robot systems

Hybrid motion control for multiple mobile robot systems