Multiple Autonomous Mobile Robots Research Articles

Formation Control of Multiple Autonomous Mobile Robots Using Turkish Natural Language Processing

People use natural language to express their thoughts and wishes. As robots reside in various human environments, such as homes, offices, and hospitals, the need for human–robot communication is increasing. One of the best ways to achieve this communication is the use of natural languages. Natural language processing (NLP) is the most important approach enabling robots to understand natural languages and improve human–robot interaction. Also, due to this need, the amount of research on NLP has increased considerably in recent years. In this study, commands were given to a multiple-mobile-robot system using the Turkish natural language, and the robots were required to fulfill these orders. Turkish is classified as an agglutinative language. In agglutinative languages, words combine different morphemes, each carrying a specific meaning, to create complex words. Turkish exhibits this characteristic by adding various suffixes to a root or base form to convey grammatical relationships, tense, aspect, mood, and other semantic nuances. Since the Turkish language has an agglutinative structure, it is very difficult to decode its sentence structure in a way that robots can understand. Parsing of a given command, path planning, path tracking, and formation control were carried out. In the path-planning phase, the A* algorithm was used to find the optimal path, and a PID controller was used to follow the generated path with minimum error. A leader–follower approach was used to control multiple robots. A platoon formation was chosen as the multi-robot formation. The proposed method was validated on a known map containing obstacles, demonstrating the system’s ability to navigate the robots to the desired locations while maintaining the specified formation. This study used Turtlebot3 robots within the Gazebo simulation environment, providing a controlled and replicable setting for comprehensive experimentation. The results affirm the feasibility and effectiveness of employing NLP techniques for the formation control of multiple mobile robots, offering a robust and effective method for further research and development on human–robot interaction.

Interoperable communication for autonomous mobile robots

The deployment of teams of autonomous mobile robots provides potential by leveraging the strengths of individual robots and compensating for their disadvantages. This makes them particularly well suited to carrying out complex scenarios for logistics, environmental monitoring or search and rescue. However, the success of such teams relies on achieving seamless interoperability among differing robots. In the area of the Internet of Robotic Things (IoRT), addressing this interoperability challenge becomes paramount. Therefore, an interoperable communication concept is introduced that considers interoperability based on semantic, syntactic, and technical clusters. It is designed to meet the specific requirements of multimodal autonomous mobile robots. Based on legal considerations, this method enables the integration and collaboration of different autonomous mobile robots in real-life applications. A logistics scenario involving multiple autonomous mobile robots illustrates the applicability of this interoperable communication concept.

A novel collaborative path planning algorithm for 3-wheel omnidirectional Autonomous Mobile Robot

Collaboration of multiple mobile robots becomes important in situations where collaborative tasks are required. For this purpose, a method including obstacle detection based on collaborative path planning of multiple Autonomous Mobile Robots (AMRs) has been developed. This study ensures the usability of collaborative omnidirectional AMRs technologies in various fields. In the study, novel path planning and obstacle avoidance algorithms are developed for collaborative mobile robots with omnidirectional mobility. Essentially, these algorithms include motion planning performed by obstacle avoidance with two identical 3-wheel omnidirectional mobile robots (TWOMR). Numerical calculations of the collaborative algorithm have been performed after the kinematic calculations, and tested algorithms developed for the proposed model. As a result, it has been observed that the path planning and obstacle avoidance algorithms developed for collaborative omnidirectional AMRs successfully follow the Master robot in the most efficient trajectory without collision and it has been observed that the developed method works with high accuracy.

Exploration of a Simple Navigation Method for Swarm Robots Pioneered by Heterogeneity

In recent years, research has been conducted on swarm robot systems in which multiple autonomous mobile robots cooperate to perform tasks. Swarm robot systems are expected to perform high functionality as a group by cooperating with each other, in spite of the limited capabilities of the individual robots. This paper explores a method of simplifying swarm robot controllers as much as possible for swarm robot navigation. If we can achieve autonomous navigation of swarm robots to a target area with minimal resource consumption, they only need to implement the task execution function in that area. This leads to lower costs for swarm robot design and more efficient system architecture design. To address the above aims, this study focuses on heterogeneity. Specifically, we introduce a navigator robot that indirectly guides swarm robots named the worker robots. Heterogeneity in this paper refers to the worker robots and the navigator robots. We design the interaction between the navigator robot and the worker robots to provide a system that guides the worker robots to the destination.

Human-Robot Cooperation: Coordinating Autonomous Mobile Robots and Human Order Pickers

In the e-commerce era, efficient order fulfillment processes in distribution centers have become a key success factor. One novel technology to streamline these processes is robot-assisted order picking. In these systems, human order pickers are supported by autonomous mobile robots (AMRs), which carry bins for collecting picking orders, autonomously move through the warehouse, and wait in front of a shelf containing a requested stock keeping unit (SKU). Once a picker has approached a waiting AMR and placed the requested SKU into the respective bin, AMR and picker may separate and move toward other picking positions. In this way, pickers continuously move between different waiting AMRs without having to return to the depot. This paper treats the coordination of multiple AMRs and multiple pickers to minimize the makespan. We present a heuristic method for the deterministic case that can handle the requirements of large e-commerce fulfillment centers and successfully solves instances with more than one thousand picking positions. Based on the obtained solutions, the performance of our picking system is compared with the traditional warehouse setup without AMR support and to another work policy using fixed pairings of picker and AMR per order. We find that largely improved makespans can be expected. In addition, we analyze the effects of stochastic picking times, speed differences between AMRs and pickers, and a zoning strategy. The ripple effect caused by stochastic picking times, in which a single delay may cascade through a tightly synchronized schedule and deteriorate picking performance, can be effectively mitigated by separating the workforce into smaller subgroups. Another important finding is that pickers and AMR should have approximately the same travel speed because slower AMRs deteriorate system performance. Finally, zoning slightly decreases the flexibility of the system and should be used if dictated by organizational reasons. History: This paper has been accepted for the Transportation Science Special Issue on Emerging Topics in Transportation Science and Logistics. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.1207 .

동적 장애물 환경에서 Heat Kernel 및 Costmap 레이어를 이용한 AMR 장애물 회피 방법

At the logistics site, interest and demand for AMR(Autonomous Mobile Robot) is increasing. A representative function required in this situation is obstacle avoidance. In particular, research on avoiding difficult or dynamic obstacles is more important. Research on this is continuously being conducted, but there is a lack of research on the case where multiple AMRs mutually avoid each other. In this study, we create a navigation costmap layer using heat kernel and propose an obstacle avoidance method based on it. The proposed method makes it difficult to approach the obstacle by adding a cost equal to the heat by applying Heat Kernel operation around it after detecting the obstacle. Since the resultant value of Heat Kernel increases rapidly as it approaches an obstacle, AMR can safely avoid obstacles or mutual avoidance.

Intuitive and Flexible Process Control for Autonomous Mobile Robots: A Case Study in a Large Logistics Enterprise

Although the usage of autonomous mobile robots (AMRs) has many advantages, the implementation of AMRs is often hindered through expensive programming, unfavorable process requirements and insufficient operator interaction possibilities. In this paper, we present an analysis of the intralogistic processes in the technical centers of a large automotive logistics enterprise and discuss the challenges of AMR implementation. Based on this analysis and our previous research on an intuitive control software, we present a concept on how to implement flexible and intuitive process control for AMRs. This includes the definition of a visual programming interface, an extended human-machine-interface (HMI) that improves communication between operators and AMRs, and a planning tool that manages multiple AMRs and operators. The results of our process analysis in the selected enterprise show that the design of the shop floor, process flexibility and the task itself, which often requires human interaction with the AMR, are challenges that hinder the implementation of current AMRs. This is mostly attributed to the AMRs requirements of a mostly static environment and process structure. Especially ad hoc changes to the process that needs to be implemented immediately are often required and cannot be realized with usual AMR software. Therefore, our interface concept strongly couples the programmed AMR routines with our HMI on mobile devices that are carried by each operator. This way, we provide flexible interaction between AMR and operators. We further discuss how we plan to implement and evaluate our proposed concepts and tools within the presented enterprise.

Immunized Token-Based Approach for Autonomous Deployment of Multiple Mobile Robots in Burnt Area

Collaborative exploration, sensing and communication in previously unknown environments with high network latency, such as outer space, battlefields and disaster hit areas are promising in multi-agent applications. When disasters such as large fires or natural disasters occur, previously established networks might be destroyed or incapacitated. In these cases, multiple autonomous mobile robots (AMR) or autonomous unmanned ground vehicles carrying wireless devices and/or thermal sensors can be deployed to create an end-to-end communication and sensing coverage to support rescue efforts or access the severity of damage. However, a fundamental problem is how to rapidly deploy these mobile agents in such complex and dynamic environments. The uncertainties introduced by the operational environment and wide range of scheduling problem have made solving them as a whole challenging. In this paper, we present an efficient decentralized approach for practical mobile agents deployment in unknown, burnt or disaster hit areas. Specifically, we propose an approach that combines methods from Artificial Immune System (AIS) with special token messages passing for a team of interconnected AMR to decide who, when and how to act during deployment process. A distributed scheme is adopted, where each AMR makes its movement decisions based on its local observation and a special token it receives from its neighbors. Empirical evidence of robustness and effectiveness of the proposed approach is demonstrated through simulation.

Nonlinear MPC for collision-free and deadlock-free navigation of multiple nonholonomic mobile robots

In this paper, we present an online nonlinear Model Predictive Control (MPC) method for collision-free, deadlock-free navigation by multiple autonomous nonholonomic Wheeled Mobile Robots (WMRs). Our proposed method solves a nonlinear constrained optimization problem at each time step over a specified horizon to compute a sequence of optimal control inputs that drive the robots to target poses along collision-free trajectories, where the robots’ future states are predicted according to a unicycle kinematic model. To reduce the computational complexity of the optimization problem, we formulate it without stabilizing terminal constraints or terminal costs. We describe a computationally efficient approach to programming and solving the optimization problem, using open-source software tools for fast nonlinear optimization and applying the multiple-shooting method. We also provide rigorous proofs of the feasibility of the optimization problem and the stability of the proposed method. To validate the performance of our MPC method, we implement it in both 3D robot simulations and experiments with real nonholonomic WMRs for different multi-robot navigation scenarios with up to six robots. In all scenarios, the robots successfully navigate to their goal poses without colliding with one another or becoming trapped in a deadlock.

Development of path planning and traffic management system in multiple autonomous mobile robots

Development of path planning and traffic management system in multiple autonomous mobile robots

基于视觉的多自主移动机器人动态编队技术研究

基于视觉的多自主移动机器人动态编队技术研究

Development of collision avoidance system for multiple autonomous mobile robots

This article presents a collision avoidance system for multiple robots based on the current autonomous car collision avoidance system. The purpose of the system is to improve the current autonomous car collision avoidance system by including data input of other vehicles’ velocity and positioning via vehicle-to-vehicle communication into the current autonomous car collision avoidance system. There are two TurtleBots used in experimental testing. TurtleBot is used as the robot agent while Google Lightweight Communication and Marshalling is used for inter-robot communication. Additionally, Gazebo software is used to run the simulation. There are two types of collision avoidance system algorithm (collision avoidance system without inter-robot communication and collision avoidance system with inter-robot communication) that are developed and tested in two main road crash scenarios, rear end collision scenario and junction crossing intersection collision scenario. Both algorithms are tested and run both in simulation and experiment setup, each with 10 repetitions for Lead TurtleBot sudden stop, Lead TurtleBot decelerate, Lead TurtleBot slower speed, and straight crossing path conditions. Simulation and experimental results data for each algorithm are recorded and tabulated. A comprehensive comparison of performance between the proposed algorithms is analyzed. The results showed that the proposed system is able to prevent collision between vehicles with an acceptable success rate.

Leader-Follower Mobile Robots Control Based on Light Source Detection

This paper deals with the leader-following control of multiple autonomous mobile robots based on a new sensing method. In this method, we have mounted a light source on the leader robot and installed a photovoltaic sensor at the front end of the follower robot. The photovoltaic sensor consisting of seven micro solar modules acts as a light sensor for the follower robot which helps it to move in accordance with the leader robot by detecting the light source of the leader robot. From the relative angle measurement and ultrasonic measurement of the relative distance, angle offset and distance information between leader robot and follower robot can be estimated. Then, based on an intuitive control method for angle steering proposed in this paper, the follower robot can be controlled smoothly to achieve leader following purpose. The new leader-following control method could overcome the disadvantages of other existing formation control methods. The experimental results show that the leader following based on light source tracking is a comparatively efficient, accurate, and cost-effective method.

Fast Scheduling of Autonomous Mobile Robots Under Task Space Constraints With Priorities

Automation is becoming more and more important to achieve high efficiency and productivities in manufacturing facilities, and there has been a large increase in the use of autonomous mobile robots (AMRs) for factory automation. With the number of AMRs increasing, how to optimally schedule them in a timely manner such that a large school of AMRs can finish all the assigned tasks within the shortest time presents a significant challenge for control engineers. Exhaustive search can provide an optimal solution. However, its associated computational time is too long to render it feasible for real-time control. This paper introduces a novel two-step algorithm for fast scheduling of AMRs that perform prioritized tasks involving transportation of tools/materials from a pick-up location to a drop-off point on the factory floor. The proposed two-step algorithm first clusters these tasks such that one cluster of tasks is assigned to one single AMR, followed by scheduling of the tasks within a cluster using a model-based learning technique. For the purpose of clustering and scheduling, a task space is defined. The results from the clustering and scheduling algorithms are compared with other widely used heuristic techniques. Both the clustering and the scheduling algorithms are shown to perform better on task sets of relevant sizes and generate real-time solutions for the scheduling of multiple AMRs under task space constraints with priorities.

State Analysis in Navigation of Multiple Autonomous Mobile Robots by Local interaction

State Analysis in Navigation of Multiple Autonomous Mobile Robots by Local interaction

Distributed Estimation and Control for Leader-Following Formations of Nonholonomic Mobile Robots

The problem of the leader-following formation control of nonholonomic mobile robots is addressed in this paper. A distributed formation control strategy using explicitly the coordination errors among robots is proposed without assuming that each follower robot knows the full state of the leader. First, a distributed estimation law is proposed for each follower robot to estimate the states, including the position, orientation, and linear velocity of the leader. The distributed formation control law is then designed based on the estimated states of the leader, and the neighborhood formation tracking error. Under some mild assumptions on the interaction graph among the leader and the follower robots, and the velocity of the leader, asymptotic convergence of formation tracking errors to zero can be achieved. Finally, some numerical simulations and experiments on a group of nonholonomic mobile robots are presented to demonstrate the effectiveness of the proposed strategy. Note to Practitioners —The motivation of this paper is to investigate a practical control strategy for the leader-following formation of multiple autonomous mobile robots subjected to nonholonomic constraints. In most of the existing leader-following formation control schemes for nonholonomic mobile robots, having access to the full state of the leader is a requirement. However, due to limitations in communication bandwidth and range, it is reasonable to assume that the information of the leader is available only to a subset of followers. Hence, this paper suggests a new distributed leader-following formation control strategy based on the distributed estimation of the leader’s states. Moreover, the coordination error between a pair of interacting robots is explicitly used in the control design to weaken the dependence on the estimated state of the leader, and enhance the decentralized nature of the proposed control scheme. The stability and convergence of the system are analyzed mathematically and the experiment using unicycles provides promising results. In ongoing research, we are addressing the issues of collision avoidance and communication delays to provide more realistic setup for the industrial applications of multivehicle systems.

Kinematics of Two-Roller-Driven Ball for RoboCup Soccer Robot

RoboCup is a competition designed to promote the research related to Artificial Intelligence (AI). W e have also organized a RoboCup soccer team “Hibikino-Musashi” and work on one of AI research topics, co-operated behavior control system using multiple autonomous mobile robots. In order to realize co-operated behavior in the soccer game, the research of ball handling system is one of the important issues capable of dribbling with a ball and passing the ball to teammate robots. In this paper, the kinematics of a two-roller-drive ball controller, which are attached in front of the soccer robot and designed to have friction on the upper side of the ball, is proposed. The forward and inverse kinematics between the ball-motion and two active rollers are derived, and the ball control mechanism has been developed and evaluated based on the results of simulations and experiments.

Cooperative formation control of autonomous underwater vehicles: An overview

Formation control is a cooperative control concept in which multiple autonomous underwater mobile robots are deployed for a group motion and/or control mission. This paper presents a brief review on various cooperative search and formation control strategies for multiple autonomous underwater vehicles (AUV) based on literature reported till date. Various cooperative and formation control schemes for collecting huge amount of data based on formation regulation control and formation tracking control are discussed. To address the challenge of detecting AUV failure in the fleet, communication issues, collision and obstacle avoidance are also taken into attention. Stability analysis of the feasible formation is also presented. This paper may be intended to serve as a convenient reference for the further research on formation control of multiple underwater mobile robots.

Fault-Tolerant Cooperative Control of Multiple Wheeled Mobile Robots Under Actuator Faults

This paper investigates fault-tolerant cooperative control (FTCC) strategies for multiple autonomous differentially-driven wheeled mobile robots (WMRs) in the presence of actuator faults during formation operation. Initially, an integrated approach with a decentralized linear model predictive control (MPC) and an input-output feedback linearization is designed and implemented on a team of WMRs in order to accomplish a formation task under normal conditions (i.e., fault-free cases). The linear model of each robot with nonlinear dynamics is found through feedback linearization, while MPC is subsequently applied to the linear model of each robot to perform the formation control. When actuator faults occur in one of the robots of the team, the faulty robot is not able to complete its assigned task anymore due to the fault, and the faulty robot has to get out from the formation mission. An FTCC strategy is designed with the tasks of the WMRs team are re-assigned to the remaining healthy vehicles to still complete the mission but with graceful performance degradation. Formation operation of the robot team is based on a leader-follower approach, while the control algorithm is implemented in a decentralized manner. Simulation results are presented to demonstrate the performance of the designed algorithm in several fault scenarios.

Formation-Based Control Scheme for Cooperative Transportation by Multiple Mobile Robots

This paper presents a motion-planning and control scheme for a cooperative transportation system comprising a single rigid object and multiple autonomous non-holonomic mobile robots. A leader-follower formation control strategy is used for the transportation system in which the object is assumed to be the virtual leader; the robots carrying the object are considered to be followers. A smooth trajectory between the current and desired locations of the object is generated considering the constraints of the virtual leader. In the leader-follower approach, the origin of the coordinate system attached to the centre of gravity of the object, which is known as the virtual leader, moves along the generated trajectory while the real robots, which are known as followers, maintain a desired distance and orientation in relation to the leader. An asymptotically stable tracking controller is used for trajectory tracking. The proposed approach is verified by simulations and real applications using Pioneer P3-DX mobile robots.