Path Planning in Multi-AGVs Using a Modified A-star Algorithm

The problem of path planning is a hot and exclusive research topic on multiple Automatic Guided Vehicles (multi-AGVs) systems. Many research results have been reported, but outrightly solving path planning problem from the perspective of reducing traffic congestion have faced obstacles. A collision-free path planning procedure based on a modified A-star Algorithm for multi-AGVs logistics sorting system is proposed in this paper. AGVs are now a poplar way to handle materials in latest smart warehouses. Many researches have been conducted and new technologies are still being developed. There is wide scale research on algorithms to help in scheduling, routing and path planning. Multi-AGVs are used to load goods automatically in a packaging factory. To ensure an effective and safe collision free path planning, this work investigates movement, scheduling and routing, speed manipulation and efficiency of machinery to target positions. The A-star algorithm with grid method to map out a typical warehouse scenario into multiple nodes was used. To have the shortest possible path, for obstacle avoidance, we employed the Braitenberg model. The waiting strategy is used for conflict resolution at intersections

Route planning of automated guided vehicles for container logistics

Automated guided vehicles (AGVs) are widely used in container terminals for the movement of material from shipping to the yard area and vice versa. Research in this area is directed toward the development of a path layout design and routing algorithms for container movement. The problem is to design a path layout and a routing algorithm that will route the AGVs along the bi-directional path so that the distance traveled will be minimized. This thesis presents a bi-directional path flow layout and a routing algorithm that guarantee conflict-free, shortest time routes for AGVs. Based on the path layout, a routing algorithm and sufficient, but necessary conditions, mathematical relationships are developed among certain key parameters of vehicle and path. A high degree of concurrency is achieved in the vehicle movement. The routing efficiency is analyzed in terms of the distance traveled and the time required for AGVs to complete all pickup and drop-off jobs. Numerical results are presented to compare performance of the proposed model. The research provides the foundation for a bi-directional path layout design and routing algorithms that will aid the designer to develop complicated path layouts

Leveraging Conflicting Constraints in Solving Vehicle Routing Problems

The Conflict-Free Electric Vehicle Routing Problem (CF-EVRP) is a combinatorial optimization problem of designing routes for vehicles to visit customers such that a cost function, typically the number of vehicles or the total travelled distance, is minimized. The CF-EVRP involves constraints such as time windows on the delivery to the customers, limited operating range of the vehicles, and limited capacity on the number of vehicles that a road segment can simultaneously accommodate.In previous work, the compositional algorithm ComSat was introduced and that solves the CF-EVRP by breaking it down into sub-problems and iteratively solve them to build an overall solution.Though ComSat showed good performance in general, some problems took significant time to solve due to the high number of iterations required to find solutions that satisfy the road segments\u27 capacity constraints. The bottleneck is the Paths Changing Problem, i.e., the sub-problem of finding a new set of shortest paths to connect a subset of the customers, disregarding previously found shortest paths. This paper presents an improved version of the PathsChanger function to solve the Paths Changing Problem that exploits the unsatisfiable core, i.e., information on which constraints conflict, to guide the search for feasible solutions. Experiments show faster convergence to feasible solutions compared to the previous version of PathsChanger

Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Autonomous guided vehicles (AGVs) are driverless material handling systems used for transportation of pallets and line side supply of materials to provide flexibility and agility in shop-floor logistics. Scheduling of shop-floor logistics in such systems is a challenging task due to their complex nature associated with the multiple part types and alternate material transfer routings. This paper presents a decision support system capable of supporting shop-floor decision-making activities during the event of manufacturing disruptions by automatically adjusting both AGV and machine schedules in Flexible Manufacturing Systems (FMSs). The proposed system uses discrete event simulation (DES) models enhanced by the Internet-of-Things (IoT) enabled digital integration and employs a nonlinear mixed integer programming Genetic Algorithm (GA) to find near-optimal production schedules prioritising the just-in-time (JIT) material delivery performance and energy efficiency of the material transportation. The performance of the proposed system is tested on the Integrated Manufacturing and Logistics (IML) demonstrator at WMG, University of Warwick. The results showed that the developed system can find the near-optimal solutions for production schedules subjected to production anomalies in a negligible time, thereby supporting shop-floor decision-making activities effectively and rapidly

A Review Of Design And Control Of Automated Guided Vehicle Systems

This paper presents a review on design and control of automated guided vehicle systems. We address most key related issues including guide-path design, estimating the number of vehicles, vehicle scheduling, idle-vehicle positioning, battery management, vehicle routing, and conflict resolution. We discuss and classify important models and results from key publications in literature on automated guided vehicle systems, including often-neglected areas, such as idle-vehicle positioning and battery management. In addition, we propose a decision framework for design and implementation of automated guided vehicle systems, and suggest some fruitful research directions

Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation

Autonomous guided vehicles (AGVs) are driverless material handling systems used for transportation of pallets and line side supply of materials to provide flexibility and agility in shop-floor logistics. Scheduling of shop-floor logistics in such systems is a challenging task due to their complex nature associated with the multiple part types and alternate material transfer routings. This paper presents a decision support system capable of supporting shop-floor decision-making activities during the event of manufacturing disruptions by automatically adjusting both AGV and machine schedules in Flexible Manufacturing Systems (FMSs). The proposed system uses discrete event simulation (DES) models enhanced by the Internet-of-Things (IoT) enabled digital integration and employs a nonlinear mixed integer programming Genetic Algorithm (GA) to find near-optimal production schedules prioritising the just-in-time (JIT) material delivery performance and energy efficiency of the material transportation. The performance of the proposed system is tested on the Integrated Manufacturing and Logistics (IML) demonstrator at WMG, University of Warwick. The results showed that the developed system can find the near-optimal solutions for production schedules subjected to production anomalies in a negligible time, thereby supporting shop-floor decision-making activities effectively and rapidly

Energy and Route Optimization of Moving Devices

This thesis highlights our efforts in energy and route optimization of moving devices. We have focused on three categories of such devices; industrial robots in a multi-robot environment, generic vehicles in a vehicle routing problem (VRP) context, automatedguided vehicles (AGVs) in a large-scale flexible manufacturing system (FMS). In the first category, the aim is to develop a non-intrusive energy optimization technique, based on a given set of paths and sequences of operations, such that the original cycle time is not exceeded. We develop an optimization procedure based on a mathematical programming model that aims to minimize the energy consumption and peak power. Our technique has several advantages. It is non-intrusive, i.e. it requires limited changes in the robot program and can be implemented easily. Moreover,it is model-free, in the sense that no particular, and perhaps secret, parameter or dynamic model is required. Furthermore, the optimization can be done offline, within seconds using a generic solver. Through careful experiments, we have shown that it is possible to reduce energy and peak-power up to about 30% and 50% respectively. The second category of moving devices comprises of generic vehicles in a VRP context. We have developed a hybrid optimization approach that integrates a distributed algorithm based on a gossip protocol with a column generation (CG) algorithm, which manages to solve the tested problems faster than the CG algorithm alone. The algorithm is developed for a VRP variation including time windows (VRPTW), which is meant to model the task of scheduling and routing of caregivers in the context of home healthcare routing and scheduling problems (HHRSPs). Moreover,the developed algorithm can easily be parallelized to further increase its efficiency. The last category deals with AGVs. The choice of AGVs was not arbitrary; by design, we decided to transfer our knowledge of energy optimization and routing algorithms to a class of moving devices in which both techniques are of interest. Initially, we improve an existing method of conflict-free AGV scheduling and routing, such that the new algorithm can manage larger problems. A heuristic version of the algorithm manages to solve the problem instances in a reasonable amount of time. Later, we develop strategies to reduce the energy consumption. The study is carried out using an AGV system installed at Volvo Cars. The results are promising; (1)the algorithm reduces performance measures such as makespan up to 50%, while reducing the total travelled distance of the vehicles about 14%, leading to an energy saving of roughly 14%, compared to the results obtained from the original traffic controller. (2) It is possible to reduce the cruise velocities such that more energy is saved, up to 20%, while the new makespan remains better than the original one

Simulation in Automated Guided Vehicle System Design

The intense global competition that manufacturing companies face today results in an increase of product variety and shorter product life cycles. One response to this threat is agile manufacturing concepts. This requires materials handling systems that are agile and capable of reconfiguration. As competition in the world marketplace becomes increasingly customer-driven, manufacturing environments must be highly reconfigurable and responsive to accommodate product and process changes, with rigid, static automation systems giving way to more flexible types. Automated Guided Vehicle Systems (AGVS) have such capabilities and AGV functionality has been developed to improve flexibility and diminish the traditional disadvantages of AGV-systems. The AGV-system design is however a multi-faceted problem with a large number of design factors of which many are correlating and interdependent. Available methods and techniques exhibit problems in supporting the whole design process. A research review of the work reported on AGVS development in combination with simulation revealed that of 39 papers only four were industrially related. Most work was on the conceptual design phase, but little has been reported on the detailed simulation of AGVS. Semi-autonomous vehicles (SA V) are an innovative concept to overcome the problems of inflexible -systems and to improve materials handling functionality. The SA V concept introduces a higher degree of autonomy in industrial AGV -systems with the man-in-the-Ioop. The introduction of autonomy in industrial applications is approached by explicitly controlling the level of autonomy at different occasions. The SA V s are easy to program and easily reconfigurable regarding navigation systems and material handling equipment. Novel approaches to materials handling like the SA V -concept place new requirements on the AGVS development and the use of simulation as a part of the process. Traditional AGV -system simulation approaches do not fully meet these requirements and the improved functionality of AGVs is not used to its full power. There is a considerflble potential in shortening the AGV -system design-cycle, and thus the manufacturing system design-cycle, and still achieve more accurate solutions well suited for MRS tasks. Recent developments in simulation tools for manufacturing have improved production engineering development and the tools are being adopted more widely in industry. For the development of AGV -systems this has not fully been exploited. Previous research has focused on the conceptual part of the design process and many simulation approaches to AGV -system design lack in validity. In this thesis a methodology is proposed for the structured development of AGV -systems using simulation. Elements of this methodology address the development of novel functionality. The objective of the first research case of this research study was to identify factors for industrial AGV -system simulation. The second research case focuses on simulation in the design of Semi-autonomous vehicles, and the third case evaluates a simulation based design framework. This research study has advanced development by offering a framework for developing testing and evaluating AGV -systems, based on concurrent development using a virtual environment. The ability to exploit unique or novel features of AGVs based on a virtual environment improves the potential of AGV-systems considerably.University of Skovde. European Commission for funding the INCO/COPERNICUS Projec

Guaranteed, Predictable, Polynomial AGV Time-Pathing

In this paper we present a framework of key algorithms and data-structures for efficiently generating timetables for any number of AGVs from any given positioning on any given graph to accomplish any given demands as long as a few easily satisfiable assumptions are met. Our proposed algorithms provide guaranteed solutions in predictable polynomial running-times, which is fundamental to any real-time application. We also develop an improved geographic reservation algorithm that provides a substantial run-time improvement of the previously best-known algorithm from $O(nm)$ to $O(n)$.Comment: 11 pages, 9 figure

Enhancing the performance of automated guided vehicles through reliability, operation and maintenance assessment

Automated guided vehicles (AGVs), a type of unmanned moving robots that move along fixed routes or are directed by laser navigation systems, are increasingly used in modern society to improve efficiency and lower the cost of production. A fleet of AGVs operate together to form a fully automatic transport system, which is known as an AGV system. To date, their added value in efficiency improvement and cost reduction has been sufficiently explored via conducting in-depth research on route optimisation, system layout configuration, and traffic control. However, their safe application has not received sufficient attention although the failure of AGVs may significantly impact the operation and efficiency of the entire system. This issue becomes more markable today particularly in the light of the fact that the size of AGV systems is becoming much larger and their operating environment is becoming more complex than ever before. This motivates the research into AGV reliability, availability and maintenance issues in this thesis, which aims to answer the following four fundamental questions: (1) How could AGVs fail? (2) How is the reliability of individual AGVs in the system assessed? (3) How does a failed AGV affect the operation of the other AGVs and the performance of the whole system? (4) How can an optimal maintenance strategy for AGV systems be achieved? In order to answer these questions, the method for identifying the critical subsystems and actions of AGVs is studied first in this thesis. Then based on the research results, mathematical models are developed in Python to simulate AGV systems and assess their performance in different scenarios. In the research of this thesis, Failure Mode, Effects and Criticality Analysis (FMECA) was adopted first to analyse the failure modes and effects of individual AGV subsystems. The interactions of these subsystems were studied via performing Fault Tree Analysis (FTA). Then, a mathematical model was developed to simulate the operation of a single AGV with the aid of Petri Nets (PNs). Since most existing AGV systems in modern industries and warehouses consist of multiple AGVs that operate synchronously to perform specific tasks, it is necessary to investigate the interactions between different AGVs in the same system. To facilitate the research of multi-AGV systems, the model of a three-AGV system with unidirectional paths was considered. In the model, an advanced concept PN, namely Coloured Petri Net (CPN), was creatively used to describe the movements of the AGVs. Attributing to the application of CPN, not only the movements of the AGVs but also the various operation and maintenance activities of the AGV systems (for example, item delivery, corrective maintenance, periodic maintenance, etc.) can be readily simulated. Such a unique technique provides us with an effective tool to investigate larger-scale AGV systems. To investigate the reliability, efficiency and maintenance of dynamic AGV systems which consist of multiple single-load and multi-load AGVs traveling along different bidirectional routes in different missions, an AGV system consisting of 9 stations was simulated using the CPN methods. Moreover, the automatic recycling of failed AGVs is studied as well in order to further reduce human participation in the operation of AGV systems. Finally, the simulation results were used to optimise the design, operation and maintenance of multi-AGV systems with the consideration of the throughputs and corresponding costs of them.The research reported in this thesis contributes to the design, reliability, operation, and maintenance of large-scale AGV systems in the modern and rapidly changing world.</div