Multiple Robot System Research Articles

Mini Rotorcraft Flight Formation Control Using Bounded Inputs

In this paper, the flight formation control and trajectory tracking control design of multiple mini rotorcraft systems are discussed. The dynamic model of a mini rotorcraft is presented using the Newton-Euler formalism. Our approach is based on a leader/follower structure of multiple robot systems. The centroid of the coordinated control subsystem is used for trajectory tracking purposes. A nonlinear controller based on separated saturations and a multi-agent consensus algorithm is developed. The analytic results are supported by simulation tests. Experimental results include yaw coordination and tracking only.

Path planning of a multiple mobile robot system

We present path-planning techniques for a multiple mobile robot system. The mobile robot has the shape of a cylinder, and its diameter, height, and weight are 8 cm, 15 cm, and 1.5 kg, respectively. The controller of the mobile robot is an MCS-51 chip, and it acquires detection signals from sensors through I/O pins. It receives commands from the supervising computer via a wireless RF interface, and transmits the status of the robots to the supervising computer via a wireless RF interface. The mobile robot system is a module-based system, and contains a controller module (including two DC motors and drivers), an obstacle detection module, a voice module, a wireless RF module, an encoder module, and a compass detection module. We propose an evaluation method to arrange the position of the multiple mobile robot system, and develop a path-planning interface on the supervising computer. In the experimental results, the mobile robots were able to receive commands from the supervising computer, and to move their next positions according to the proposed method.

Navigation strategy of multiple mobile robot systems based on the null-space projection method

This paper deals with a navigation algorithm for swarm robot systems in which multiple mobile robots work together. The motion of each mobile robot is modeled in such a way to have more inputs than the number of outputs. The null-space projection method of this model is employed to resolve the motion of the swarm robot system while avoiding obstacles. The feasibility of the proposed navigation algorithm is verified through a simulation study using several swarm robot models.

Multiple-Robot Systems for USAR: Key Design Attributes and Deployment Issues

The interaction between humans and robots is undergoing an evolution. Progress in this evolution means that humans are close to robustly deploying multiple robots. Urban search and rescue (USAR) can benefit greatly from such capability. The review shows that with state of the art artificial intelligence, robots can work autonomously but still require human supervision. It also shows that multiple robot deployment (MRD) is more economical, shortens mission durations, adds reliability as well as addresses missions impossible with one robot and payload constraints. By combining robot autonomy and human supervision, the benefits of MRD can be applied to USAR while at the same time minimizing human exposure to danger. This is achieved with a single-human multiple-robot system (SHMRS). However, designers of the SHMRS must consider key attributes such as the size, composition and organizational structure of the robot collective. Variations in these attributes also induce fluctuations in issues within SHMRS deployment such as robot communication and computational load as well as human cognitive workload and situation awareness (SA). Research is essential to determine how the attributes can be manipulated to mitigate these issues while meeting the requirements of the USAR mission.

Decentralized deployment with obstacle avoidance for AUVs

AbstractIn multiple robotic system, the deployment problem consists in the optimal placement of the robots within a given environment. In this paper, a fully decentralized strategy, based on the so called Null-Space-based Behavioral control is proposed. The chosen behavioral approach allows to handle the eventual presence of obstacles in the environment in a task-priority fashion thus surmounting mono-task classical approaches. Numerical simulations confirm the validity of the proposed deployment strategy.

On Designing a Cooperative Control System for Multiple Mobile Robots to Locate the Source of Odor

AbstractThis paper deals with the problem of odor source localization using a multi-robot system. A cooperative control system, which can coordinate the multi-robot system to locate the source of odor, is designed and independently executed by each robot. The proposed cooperative control system consists of three levels. In the first level, based on a mixture ensemble Kalman filtering theory, a new cooperative search algorithm, which can predict the probable position of the odor source by exploiting the information among the multi-robot system, is proposed. In the second level, a trajectory planning algorithm, by which the next position of a robot can be generated according to the predicted position of the odor source, detection events and nondetection events, is developed. In the third level, a consensus algorithm is used to control the robot to move toward the next position. Finally, the performance capabilities of the proposed cooperative control system are illustrated for the problem of odor source localization.

A Stable Formation Control Using Approximation of Translational and Angular Accelerations

In this paper, a stable leader-following formation control for multiple non-holonomic mobile robot systems using only limited on-board sensor information is proposed. The control can be used for the conventional single leader – single follower (SLSF) or for novel two leaders – single follower (TLSF) schemes. The control algorithm utilizes estimations of the leaders' translational and angular accelerations in a simple form to reduce the measurement of indirect information. Simulation results show that the TLSF scheme can suppress the oscillation and damping in formation of large robot teams.

Trajectory Tracking for a Group of Mini Rotorcraft Flying in Formation

AbstractIn this paper, we study the problem of flight formation control and trajectory tracking control for a group of mini rotorcraft. The goal is to achieve and maintain a stable formation for multiple mini rotorcraft while guaranteeing the tracking of a desired time-varying reference. A two-level controller is developed where a individual control strategy guarantees the stabilization of each mini rotorcraft and a collective control strategy ensures a geometric formation and trajectory tracking. A nonlinear controller based on separated saturations is used as a individual controller to stabilize every mini rotorcraft. In order to achieve a collective behavior, i.e. formation and trajectory tracking, we adopt a leader/follower structure of multiple robot systems. The resulting system allow us to use the centroid of the coordinated control subsystem for trajectory tracking purposes. After a initial transient in which every mini rotorcraft will lock himself to the desired geometric formation, then the center of mass which will converge to the desired trajectory while keeping a stable formation. The analytic results are supported by simulation tests.

An Active Cooperative Observation Method for Multi-robots in Three Dimensional Environments

The solution to multiple mobile robot systems actively and cooperatively observing a moving target (MACO) means the algorithm that tries to pursuit optimal (sub-optimal) observations of the moving target by simultaneously fusing the observational data from multiple robot systems and regulating their behaviors cooperatively. In this paper, the 3D MACO method with two robots is studied. First, at the basis of extended set-membership filter (ESMF), a high precise observation fuse method is presented through combining the information fuse process and the set operations in ESMF algorithm. The new algorithm is as fast as the single ESMF algorithm since it has almost the same computational burden. Second, a coordinate behavior optimization method is given by combining the concept of optimal observational angle and the relative velocity coordinates (RVC) planning method. By using the RVC method, the coordinate behavior optimization can be transferred into a linear planning (LP) problem, which makes its real time application possible. Finally, 3D moving target observational simulations are conducted to verify the feasibility and validity of the proposed algorithm.

Cellular ants: A method to create collision free trajectories for a cooperative robot team

Creating collision-free trajectories for mobile robots, known as the path planning problem, is considered to be one of the basic problems in robotics. In case of multiple robotic systems, the complexity of such systems increases proportionally with the number of robots, due to the fact that all robots must act as one unit to complete one composite task, such as retaining a specific formation. The proposed path planner employs a combination of Cellular Automata (CA) and Ant Colony Optimization (ACO) techniques in order to create collision-free trajectories for every robot of a team while their formation is kept immutable. The method reacts with obstacle distribution changes and therefore can be used in dynamical or unknown environments, without the need of a priori knowledge of the space. The team is divided into subgroups and all the desired pathways are created with the combined use of a CA path planner and an ACO algorithm. In case of lack of pheromones, paths are created using the CA path planner. Compared to other methods, the proposed method can create accurate collision-free paths in real time with low complexity while the implemented system is completely autonomous. A simulation environment was created to test the effectiveness of the applied CA rules and ACO principles. Moreover, the proposed method was implemented in a system using a real world simulation environment, called Webots. The CA and ACO combined algorithm was applied to a team of multiple simulated robots without the interference of a central control. Simulation and experimental results indicate that accurate collision free paths could be created with low complexity, confirming the robustness of the method.

Adaptable User Interface Based on the Ecological Interface Design Concept for Multiple Robots Operating Works with Uncertainty

Problem statement: When supervising a team of semi-autonomous robots, the operator’s task is not only the manipulation of each robot but also achievement of the top goal that is assigned to the entire team of humans and robots. The operators are demanded to comprehend highly complex states and make appropriate decisions in dynamic environment using the limited cognitive resources. The Ecological Interface Design (EID) is a design approach based on visualization of constraints in study environment onto the interface to reduce the cognitive workload. Our research question was “How should we design Human-Robot Interface (HRI) that allows operators to understand states of multiple robots systems working in environment with uncertainty?” Approach: Our proposed method was Adaptable User Interface (AUI) with EID. The interface is a framework that allowed the operators to take selectable use of displays indicating different types of functional information. Two types of expressions of functions were defined for indicating states of functions: indication of functional disposition and of effectiveness. Three cognitive experiments were conducted to reveal potential efficacy of the method using an experimental test-bed simulation. Results: The results of the first and second experiments showed that usefulness of functional indications is different from different works, tasks and operators. The third experiment demonstrated that operators could select and use appropriate information among a set of indicators with different types and levels of functional information, which are adaptive for tasks, their strategies, their skills and available information and knowledge about the tasks. Conclusion: From the remarks, it can be concluded that the proposed method (AUI+EID) is a useful and feasible HRI method for multiple robot operations, even knowledge about the work is not sufficient to build a set of dedicated indicators each has only necessary information for a situation.

SEBUAH MODEL BERBASIS PENGETAHUAN UNTUK PENGENDALIAN FORMASI SISTEM ROBOT MAJEMUK

Study of multi-robot system has been popular in recent years. This system is able to reduce processing time of some processes, the cost and complexity of the system. However, multi-robot system also has some problems. One of the problems faced by these systems is how to control robots in a certain formation when carrying out its functions. Several methods have been offered to resolve the existing problems. This study tries to offer a method to solve the problem, by modeling the multi-robot systems and implement a control system in order to maintain a specific formation. The study attempted to use a controller based on knowledge base system. Model is developed using MATLAB software and simulated to determine the performance. Several experiments are conducted to determine the movement of the robot and its ability to maintain a specific formation. From the experiments it can be said that the modeling of multiple-robot system has been reliable. In addition, formation control actions have also been running well, although there should be further development.

Collective unary decision-making by decentralized multiple-robot systems applied to the task-sequencing problem

When a complex mission must be undertaken, it often can be simplified by dividing it into a sequence of smaller subtasks, which are then completed in order. This strategy implicitly requires a system to recognize the completion of each subtask and make the decision to begin work on the next one. Decentralized multiple-robot systems can tackle many tasks, but their behavior is typified by continuous responses to stimuli. Task sequencing, however, demands a controlled, self-induced phase change in collective behavior—working on one task one moment and then on a different task the next—which is nontrivial for an emergent system. The main contribution of this study is a collective decision-making framework for decentralized multiple-robot systems that enables such a system to cooperatively decide that a current task has been completed and thus focus its attention on the next one in a sequence using only anonymous local communication. Central to the framework is the use of consensus, whereby task sequencing is delayed until a prespecified proportion of a system’s robots agree that the current task is complete, reducing the likelihood of premature decisions. Two low-cost consensus estimation strategies are presented, both of which are practical for the extremely simple robots that are expected to compose large decentralized systems. Experiments in simulation and with real robots demonstrate that the proposed decision-making framework performs as predicted. Although the specific application of collective decision-making in this work is the cooperative task-sequencing problem, the proposed decision-making framework potentially has many additional applications.

Workspace mapping based on multisensor information fusion using heterogeneous onboard sensors

In recent years, multiple robot systems that perform team operations have been developed. These robot systems are expected to execute complicated tasks smoothly in a given congested workspace. In this article, we propose a workspace mapping algorithm using ultrasonic stereo sonar and an image sensor in order to operate the mobile robots among obstacles. This workspace mapping algorithm involves two steps: (1) the position detection of obstacles using ultrasonic stereo sonar, and (2) the shape detection of obstacles using an image sensor. While each robot moves around in the given workspace, the two steps of the mapping algorithm are repeated and sensor data are collected. The robot measures the distance and the direction of obstacles using ultrasonic stereo sonar. The shape of obstacles is also captured using an onboard image sensor. A workspace map is created based on the sensor data accumulated from the proposed method, and successful results are also obtained through experiments.

Situation Awareness and Team Communication in Robot Control

Operator performance in robotics tasks is impacted by the situation awareness (SA) that individuals or teams are able to acquire and maintain on the robot, the associated environments, and the tasks to be completed. SA can be influenced by team processes when multiple humans must work together for coordinating control of multiple robotic systems. In this study, we investigated the relationship between SA and team verbal communications in a collaborative robotics tasks involving robots under semi-autonomous control. Results indicate that the content, format, and amount of communication can significantly impact operator SA and task performance.

Ad Hoc Wireless Networking and Shared Computation for Autonomous Multirobot Systems

A wireless ad hoc network is introduced that enables inter-robot communication and shared computation among multiple robots with PC/104-based single board computers running the real-time application interface patched Linux operating system. Through the use of IEEE 802.11 ad hoc technology and User Datagram Protocol, each robot is able to exchange data without the need of a centralized router or wireless access point. The paper presents three key aspects of this novel architecture to include: 1) procedures to install the real-time application interface patched operating system and wireless ad hoc communication protocol on a multiple robot system; 2) development of a Simulink ® library to enable intercommunication among robots and provide the requisite software-hardware interfaces for the onboard sensor suite and actuator packages; 3) methods to rapidly generate and deploy real-time executables using Mathwork’s Real-Time Workshop™ to enable an autonomous robotic system. Experimental test results from the Spacecraft Robotics Laboratory at the Naval Postgraduate School are presented which demonstrate negligible network latencies and real-time distributed computing capability on the Autonomous Spacecraft Assembly Test Bed. A complete manual is also included to replicate the network and software infrastructures described in this work. Also, the developed Simulink ® library can be requested from the authors.

Cooperative Decision-Making in Decentralized Multiple-Robot Systems: The Best-of-N Problem

Multiple-robot systems (MRS) that are decentrally organized have many benefits over centralized systems. Decentralized systems are less affected by computational and communicative bottlenecks, and they are more robust to the loss of individual member robots. System-level cognitive operations, though, are much more difficult to implement in decentralized systems. One example is the best-of-N decision-making problem, in which a team attempts to unanimously select a single alternative from a list that maximizes a given metric. This is a valuable operation, since many system-level operations can be expressed in this form. Optimal best-of-N decision-making, however, is intractable in large decentralized systems. The contribution of this paper is a biologically inspired algorithm that enables a decentralized MRS composed of very simple robots to make good, unanimous decisions. In a series of physical experiments using real robots, the best decision was made at least 80% of the time. In all, 100% of the decisions achieved perfect consensus, which prevented the MRS from becoming fragmented. The decisions are made using anonymous, local communication, with no direct comparisons of the available alternatives by the individual robots.

Multiple robot / single human interaction: effects on perceived workload

This paper presents results from a user evaluation of a real multiple robot system in which the human's perceived workload and performance were measured. Participants completed tasks with one, two and four real heterogeneous mobile ground-based robots for indoor material transportation tasks. Twelve participants completed four trials of each task over two days. Generally speaking, little difference was found between the one- and two-robot tasks; however, perceived workload significantly increased while performance decreased during the four-robot task. A correlation analysis found that perceived workload increased as the number of commands (in total and by command type) and completion times increased. The highest number of accidents and user errors occurred during the four-robot task. In order to increase the number of robots a single human can supervise, the human must be provided with capabilities that reduce the number of required commands while also optimising the human's interactions with the robots.

A CORBA‐based cooperative mobile robot system

PurposeThe purpose of this paper is to present a distributed multiple mobile robot system that provides a collaborative control and simulation environment.Design/methodology/approachA CORBA‐based cooperative system is designed to implement a robotic layered cooperative mechanism. The mechanism has three layers: mission, transport and execution. In order to realize a flexible and effective communication in the cooperative mechanism, an extended robot event service (federated event service) is proposed to improve the cooperative system's real time performance.FindingsExperimentation has proved the validity and effectiveness of the system. The federated event service's latency is approximately 9 percent less than the standard event service latency when the CPU is determined.Practical implicationsThe robotic modularized system includes the map‐building, path‐planning, robot task‐planning, simulation and actual robot control function modules, and uses CORBA to integrate the whole system. It is easy to implement a layered cooperative mechanism for multiple mobile robots. Given the problem on multiple robots cooperation latency, a useful extended robot event service is proposed.Originality/valueThe paper focuses on the distributed functional modular architecture, and the multiple robots cooperative layered mechanism. In the mechanism, an extended robot event service (federated event service) is proposed to reduce the cooperative system's real time latency. The conducted experiment validates the proposed system with a good performance for multiple mobile robots' cooperation.

複数移動ロボットによる搬送作業における衝突予測に基づく経路計画法(機械力学,計測,自動制御)

Multiple robot system with decentralized control attracts attention and is expected to play an important role in transportation systems in factories and warehouses. In transportation systems, it is necessary to plan a route that minimizes the transportation time with less collision and deadlock. The goal of this study is to calculate appropriate routes with reducing communication load and computational load. In this paper, we proposed to combine prior route planning and local avoidance. In order to reduce computational load, each robot predict probability of collision with other robots by comparing present and destination position. A route with less collision is calculated by reflecting the overlap of route which has probability of collision into dijkstra method. The proposed method is evaluated through the computer simulation and the experiment using real robots.