Multiple Robot System Research Articles

CloudThinking as an Intelligent Infrastructure for Mobile Robotics

Mobile robotics is a transforming field that presents a varying set of challenges. The discussion on the autonomy of (self-powered) robots is not settled, and as the communication infrastructure evolves, centralized concepts become more attractive over distributed concepts. This paper presents the CloudThinking architecture applied to intelligent cloud-based robotic operation. CloudThinking offloads most of complex robotic tasks to a central cloud, which retrieves inputs from the environment as a whole in order to instruct the robots to perform its actions. CloudThinking is a natural approach to the orchestration of multiple specialized robotic systems, defining the best mechanisms for reaching a goal. Furthermore, this architecture provides a set of automatic features which can be useful for application developers. These features can fully exploit novel cloud tools development as it becomes available, providing a time-resilient infrastructure of easy upgrade. The resulting approach has the potential to create a different set of market for robotic application developers.

A Cooperative Path Planning Algorithm for a Multiple Mobile Robot System in a Dynamic Environment

A practical path planning method for a multiple mobile robot system (MMRS) requires handling both the collision-free constraint and the kinematic constraint of real robots, the latter of which has to date been neglected by most path planning methods. In this paper, we present a practical cooperative path planning algorithm for MMRS in a dynamic environment. First, each robot uses an analytical method to plan an obstacle-avoidance path. Then, a distributed prioritized scheme is introduced to realize cooperative path planning. In the scheme, each robot calculates a priority value according to its situation at each instant in time, which will determine the robot's priority. Higher-priority robots can ignore lower-priority robots, whereas lower-priority robots should avoid collisions with higher-priority robots. To minimize the path length for MMRS, a least path length constraint is added. The priority value is also calculated by a path cost function that takes the path length into consideration. Unlike other priority methods, the algorithm proposed is not time consuming; therefore, it is suitable for dynamic environments. Simulation results are presented to verify the effectiveness of the proposed algorithm.

Flexible and continuous execution of real-time critical robotic tasks

Today, industrial robots are usually programmed using specialised programming languages, different for every robot manufacturer. These languages provide good usability, because they are tailored to the functionality traditionally offered by robots. However, these languages are reaching their limits with the growing integration of sensors or multiple robot systems. Therefore, we propose an architecture based on the separation of application control and the execution of real-time robotic tasks. This article describes a flexible and extensible interface for the specification and continuous execution of robotic tasks.

Synchronized control with neuro-agents for leader–follower based multiple robotic manipulators

In this paper, a new neural network enhanced synchronized control approach is proposed for multiple robotic manipulators systems (MRMS) based on the leader–follower network communication topology. The justification of introducing two adaptive Radial Basis Function Neural Networks (RBF NN), also called neuro-agents, is to facilitate the whole control system design and analysis. Otherwise such design is impossible with classical analytical procedure. The first agent is the neuro-compensator to accommodate uncertainty associated with the follower manipulators, and the second agent is the neuro-estimator to obtain acceleration of the leader manipulator. Correspondingly the stability analysis of the designed control system is formulated with Lyapunov method. Finally numerical bench tests under various critical conditions are conducted to validate the effectiveness of the proposed approach.

A combined robot selection and scheduling problem for flow-shops with no-wait restrictions

This paper addresses a bicriteria no-wait flow-shop scheduling problem with multiple robots transferring jobs between pairs of consecutive machines. The robots share an identical track positioned alongside the machine transfer line. Each robot is assigned to a portion of the tract from which it performs job transfers between all reachable machines. We assume that job processing times are both machine and job independent, that jobs are not allowed to wait between two consecutive machines and that machine idle times are not allowed. We define a combined robot selection and scheduling problem (RSSP) for a set of Q non-identical robots characterized by different costs and job transfer and empty movement times. A solution to the RSSP problem is defined by (i) selecting a set of robots, (ii) assigning each robot to a portion of the track, and (iii) scheduling the robot moves. We define a robot schedule as feasible if all the jobs satisfy the no-wait condition and there are no machine idle times. The quality of the solutions are measured by two criteria (performance measures): makespan and robot selection cost. We study four different variations of the RSSP,one which is shown to be solvable in polynomial time while the other three turn out to be NP-hard. For the NP-hard, we show that a pseudo-polynomial time algorithm and a fully polynomial approximation scheme exists, and derive three important special cases which are solvable in polynomial time. The RSSP has aspects of robot selection, machine-robot assignment and robot movement scheduling. We believe this is the first time that this type of problem has been treated in the literature, and addresses a very important problem in multiple robotic systems operation. Our contribution lies in the formulation, methodology, algorithms for solution and complexity results which jointly treats all aspects of the problem simultaneously without the need to defer to heuristic decomposition methods.

군집로봇을 위한 다중 코드 초음파센서의 코드조합 최적화

In multi-robot systems, ultrasonic sensors are widely used for localization and/or obstacle detection. However, conventional ultrasonic sensors have a drawback, that is, the interference problem among ultrasonic transmitters. There are some previous studies to avoid interferences, such as TDMA (Time Division Multiple Access) and CDMA (Code Division Multiple Access). In multiple autonomous mobile robots systems, the Doppler-effect has to be considered because ultrasonic transceivers are attached to the moving robots. To overcome this problem, we find out the ASK (Amplitude Shift Keying)-CDMA technique is more robust to the Doppler-effect than the BPSK (Binary Phase Shift Keying)-CDMA technique. In this paper, we propose a new code-expression method and a Monte-Carlo based algorithm that optimizes the ultrasonic code combination in the ASK-CDMA ultrasonic system. The experimental results show that the proposed algorithm improves the performance of the ultrasonic multiple accessing capacity in the ASK-CDMA ultrasonic system.

초음파 센서를 이용한 다수의 이동형 개체 위치 추적시스템 개발에 관한 연구

본 논문은 시뮬레이션을 통해 다수의 초음파 발신부로부터 순차적으로 발생되는 초음파를 공간 내에서 자유롭게 움직이는 여러개의 이동형 개체들에 각각 장착된 초음파 수신부가 수신하여 각 개체의 위치를 스스로 계산할 수 있는 시스템을 제안한다. 이 시스템은 적절한 위치에 고정 장착된 3개 이상의 초음파 발신부에 의해 정의되는 공간 내에서 움직이는 개체가 자신들의 위치를 스스로 추정 가능하게 하기 때문에 공간 내에 존재하는 개체 수에 제안을 받지 않는 다는 장점이 있다. 따라서 본 기술은 다 개체 시스템의 위치 제어 및 모션 포착 기술에 효과적으로 응용이 가능하다. In This paper, through simulation, proposes a system which makes it possible for freely moving multiple agents with ultrasonic receivers to estimate their own position by themselves using the ultrasonic signals sequentially emitted from multiple ultrasonic transmitters. This system possesses an advantage that there is no limit in the number of agents existing in the space covered by more than three transmitters fixed at proper locations. Hence, the proposed system can be utilized effectively in position tracking control of multiple robotic agents system and motion capturing system.

Application of Mobile Robot System for Cell Production

In this paper, we have discussed on the performance of the knowledge sharing for the multiple robot system which is equipped with the advanced telecommunication devices. This has enabled the mobile robots to perform advanced communication. We propose the utilization of the knowledge sharing robot system at manufacturing scenes, and demonstrate the performance by a simplified simulation. Applying this knowledge sharing system, which helps to improve the balance of the line, the improvement of the productivity and quality was observed. Consequently, the cost reduction and improvement of the efficiency shall be expected by introducing more sophisticated algorithm of knowledge sharing and distribution.

Multiple mobile robots system with network-based subsumption architecture

In this paper, a unique multiple mobile robots system is proposed to enable engineering students and engineers in the field to efficiently learn subsumption architecture and develop swarm intelligence. The subsumption architecture is known as one of the behaviour-based artificial intelligence. Each of multiple mobile robots within the system has three wheels driven by DC motors and six position sensitive detector (PSD) sensors. Network-based subsumption architecture is considered to realise a schooling behaviour by using only information from the PSD sensors. Further, a server supervisory control is introduced for poor hardware platforms with limitations of software development, i.e., the mobile robots can only behave based on the most simply subdivided reaction behaviours, i.e., reflex actions, generated from agents. Experimental results show interesting behaviour among the multiple mobile robots, such as following, avoidance and schooling.

Heuristic based Task Allocation Algorithm for Multiple Robots Using Agents

Task allocation plays an important role in achieving high utilization of robots in multiple robots system. Existing task allocation schemes do not consider the dynamic and unpredictable nature of the environment and try to maximize the robot synergism in order to achieve various objectives such as minimization of turnaround time, make span, and cost. Here the methodology for task allocation using a set of static and mobile agents controlling a pool of multiple robots is presented and the objective is to minimize the turnaround time. The agents are capable of autonomous decision making and thus make autonomous task allocation decisions based on the changing status of the robot system. Also, the agents are used for delivering the task and collecting the results in two separate trips thus avoiding the waiting time, which in turn helps to minimize the turnaround time. The performance of the algorithm is assessed by comparing with other existing task allocation method. The numerical simulation results manifest that the proposed algorithm performs the best under different problem scales and connectivity.

Cooperative Control System of Multiple Mobile Robots Using Particle Swarm Optimization with Obstacle Avoidance for Tracking Target

Cooperative Control System of Multiple Mobile Robots Using Particle Swarm Optimization with Obstacle Avoidance for Tracking Target

A Packet Loss Compliant Logic-Based Communication Algorithm for Cooperative Path-Following Control

We introduce an event driven communication logic for decentralized control of a network of robotic vehicles (agents). The strategy proposed is robust to packet losses and drives the vehicles to predefined paths while holding a desired geometric formation pattern. To this effect, the paper extends an existing cooperative path following framework to consider the practical case where communications among the vehicles occur at discrete instants, instead of continuously. The introduced communication logic takes into account the topology of the communication network, the fact that communications are discrete, and the cost of exchanging information. We also address explicitly communication losses and bounded delays. Conditions are derived under which the overall closed loop system is input-to-state practically stable. The communication logic is applied to a cooperative path-following control system of multiple underactuated autonomous marine robots. Simulation results are presented and discussed.

A Survey and Analysis of Multi-Robot Coordination

In the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper.

Co-localization of Non-cooperative Targets Based on Multiple Space Robot System

According to the characteristics of relative measurement elements in the on-orbit servicing system with multiple space robots,a non-cooperative target co-localization strategy based on distributed filters is proposed.Firstly,the mission of non-cooperative target co-localization based on multiple space robots is defined,and a co-measurement model is also established.After that,a general expression of relative dynamics of multiple space robots is derived,and a centralized co-localization filter is designed.In order to reduce the computation load of iteration process in filtering,a co-localization method based on distributed filters is proposed.The stabilities of both filters are evaluated with linear system observability theory.Finally,a real-time semi-physical simulation system is established,and the co-location strategy based on distributed filters is simulated.The high stability and accuracy of the co-localization strategy are demonstrated by simulations.

Research on Cooperation Localization and Mapping for Hoisting Multi-Robot System

According to the practical operation of the hoisting multi-mobile robots system (HMRS), the cooperation localization and mapping is studied. Firstly, an improved algorithm of cooperation localization solution of multiple robot system is proposed based on map gridding algorithm. In addition, by virtue of sensor technology, the grid method is designed, which has the ability of accurate, reliable localization and rapid local mapping of the HMRS. Finally, simulation results demonstrate that the localization and mapping system is feasible and efficient.

A proposal of experimental education system of mechatronics

Recently, many studies on educational system are being conducted. In this manuscript, a unique education system is proposed for mechanical engineers to be able to efficiently learn basic mechatronics techniques. The system is composed of three subsystems. The first subsystem is used to learn input/output port operations, periodically LED lights ON/OFF and a stepping motor control. The second subsystem is effective to learn AD transformation for several sensor information, DA transformation for DC motor control and a PID control method. Further, the third subsystem is multiple mobile robots system to learn the subsumption architecture for schooling behavior. The effectiveness of the proposed systems was confirmed through experimental instructions in Tokyo University of Science, Yamaguchi.

Performance Optimisation of Mobile Robots for Search-and-Rescue

This paper presents a team performance optimisation system for multiple mobile robots in search-and-rescue operations, in which refugees are first discovered and subsequently robots are dispatched to transport themto shelters. Coordination of mobile robots involves two fundamental issues, namely task allocation and motion planning. While task allocation assigns jobs to robots, motion planning generates routes for robots to execute the assigned jobs. Task allocation and motion planning together play a pivotal role in optimisation of the robot team performance. These two issues become more challenging in dynamic search-and-rescue environments, where the refugees are unpredictably discovered at different locations and the traffic conditions of rescue zones keep changing. Weaddress these two issues by proposing an auction-based closed-loop module for task allocation and a bio-inspired intelligent module for motion planning. The task allocation module is characterised with a closed-loop bid adjustment mechanism to improve the bid accuracy even in light of stochastic rescue requests. The motion planning module is bio-inspired intelligent in that it features detection of imminent neighbours and responsiveness of virtual force navigation in dynamic traffic conditions. Simulations show that the proposed system is a practical tool to optimise the dynamic operations of search-and-rescue by a team of mobilerobots.

Position synchronised control of multiple robotic manipulators based on integral sliding mode

In this study, a new position synchronised control algorithm is developed for multiple robotic manipulator systems. In the merit of system synchronisation and integral sliding mode control, the proposed approach can stabilise position tracking of each robotic manipulator while coordinating its motion with the other manipulators. With the integral sliding mode, the proposed approach has insensitiveness against the lumped system uncertainty within the entire process of operation. Further, a perturbation estimator is proposed to reduce chattering effect. The corresponding stability analysis is presented to lay a foundation for theoretical understanding to the underlying issues as well as safely operating real systems. An illustrative example is bench tested to validate the effectiveness of the proposed approach.

Shared Control : Balancing Autonomy and Human Assistance with a Group of Quadrotor UAVs

Robustness and flexibility constitute the main advantages of multiple-robot systems with respect to single-robot ones as per the recent literature. The use of multiple unmanned aerial vehicles (UAVs) combines these benefits with the agility and pervasiveness of aerial platforms [1], [2]. The degree of autonomy of the multi-UAV system should be tuned according to the specificities of the situation under consideration. For regular missions, fully autonomous UAV systems are often appropriate, but, in general, the use of semiautonomous groups of UAVs, supervised or partially controlled by one or more human operators, is the only viable solution to deal with the complexity and unpredictability of real-world scenarios as in, e.g., the case of search and rescue missions or exploration of large/cluttered environments [3]. In addition, the human presence is also mandatory for taking the responsibility of critical decisions in high-risk situations [4].

Closed-Curve Path Tracking for Decentralized Systems of Multiple Mobile Robots

In this paper we address the problem of making a group of mobile robots cooperatively track an assigned path. We consider paths described by completely arbitrarily shaped closed curves. The proposed control strategy is a fully decentralized algorithm and it does not require any global synchronization. The desired behavior is obtained by means of some properly designed artificial potential functions. Analytical proofs are provided to show the asymptotic convergence of the system to the desired behavior. Matlab simulations and experiments on real robots are described as well for validation purposes.