Guided Vehicle System Research Articles

Model and Algorithm for Co-scheduling of Stackers and Single RGV during retrieval Process in AS/RS

This paper studies the co-scheduling problem of the stackers and single rail guided vehicle system in automated storage and retrieval systems. We formulate the problem into a mixed integer linear programming model with the aim of minimizing the total retrieval time. In order to solve the problem, an improved genetic algorithm is proposed, and the properties of the optimal solution are applied to improve the offspring chromosomes. A lower bound of the total retrieval time is developed. The numerical experiment indicates that the proposed algorithm can solve the problem effectively. Compared with the solutions obtained by using first come first served, the total retrieval time obtained by the proposed algorithm is reduced by an average of 8.36%. The average deviation from the lower bound is 2.00%.

Development of a Hybrid Simulator for Underwater Vehicles With Manipulators

This article describes a hybrid simulation approach meant to facilitate the realization of a simulator for underwater vehicles with one or more manipulators capable of simulating the interaction of the vehicle with objects and structures of the environment. The hybrid simulation approach is first described and motivated analytically, then an analysis of simulation accuracy is proposed, where, in particular, the implications of added mass simulation are discussed. Then, a possible implementation of the proposed architecture is shown, where a robotic simulator of articulated bodies, capable of stable and accurate simulation of contact forces, although unfit to simulate any serious hydrodynamic model, is tightly interfaced with a general purpose dynamic systems simulator that is used to simulate the hydrodynamic forces, the vehicle guidance, navigation, and control system, and also a man–machine interface. Software details and the technicalities needed to interface the two simulators are also briefly presented. Finally, the results of the simulation of three operational scenarios are proposed as qualitative assessment of the simulator capabilities.

Optimal Petri-Net Controller for Avoiding Collisions in a Class of Automated Guided Vehicle Systems

Automated guided vehicles (AGVs) are being extensively used for transportation and distribution of materials due to their high-efficiency. However, the vehicle-collision free problem is challenging since, when modeling these systems, there are indistinguishable and uncontrollable events due to the limited sensors and actuators. This paper proposes an approach to the design of a maximally permissive (optimal) controller to prevent vehicles from any collision based on Petri nets (PNs). For a typical class of AGV systems, a system modeling algorithm is presented using labeled PN, where indistinguishable events are represented by a set of transitions carrying the same label, and an uncontrollable event by an uncontrollable transition. By virtue of the PN model, the collision-free problem is formalized as a conjunction of linear constraints that are converted into admissible ones by an algorithm such that the computational overhead due to uncontrollable events is significantly reduced. In turn, a method is developed to compute the set of consistent markings for an observed sequence of labels that represent signals generated by sensors. Finally, given an observed sequence, a maximally permissive control action is computed to enforce a conjunction of admissible linear constraints based on the set of consistent markings. The approach well addresses the challenging issues caused by indistinguishable and uncontrollable events. A typical AGV system is utilized to illustrate and verify the theoretical results throughout the work.

Design of magnetic navigation automatic guided vehicle system

Automatic Guided Vehicle is an automatic transportation robot with high universality and diversity which can drive and transport goods automatically in the established path, so it is widely used in mass production and logistics industry. In this paper, an AGV system with independent guidance and integrated network control is designed and developed. Firstly, based on the project requirements of some company and the practical problems, the basic parameters of AGV are determined, and the movement analysis of AGV is carried out to obtain its motion characteristic equation for movement control. Then the hardware of the mechanical and electronic parts of the AGV is designed. Keil uVision 5 is used for software programming. Based on the core PID algorithms, the related algorithms design of AGV paths recognition and the movement control are presented. Finally, a small AGV capable of carrying a maximum weight of 8KG is trial-produced and tested. The test data show that the position deviation can be controlled within 15mm and the maximum speed can reach 1m/s. It can communicate with the host computer in various ways. Its expansibility, stability, accuracy and real-time performance all meet the requirements of the project.

A Robust Model-Predictive Guidance System for Autonomous Vehicles in Cluttered Environments

This paper proposes a system for guidance of autonomous vehicles based on a generalized robust model-predictive control (R-MPC) technique. It offers two scenarios, in which R-MPC is used to provide optimized motion plans guaranteed to satisfy constraints and avoid obstacles in the presence of bounded uncertainty. The first scenario involves a military unmanned aerial vehicle flying over a target, while avoiding enemy defenses. The second scenario involves an assistive care robot safely navigating to waypoints throughout a cluttered home. In each case, obstacles are represented as a collection of linear inequality constraints that adapt to changes in the environment. Results show that when R-MPC is formulated using a series of positive-semidefinite relaxations on linear inequality constraints, safe optimum trajectories can be planned by solving a convex quadratic program. When formulated in terms of perturbations on feedback predictions, this solution is guaranteed to be robustly stable.

New Automated Guided Vehicle System Using Real-Time Holonic Scheduling for Warehouse Picking

We propose a new robotic system using an automated guided vehicle (AGV) for order picking in logistics warehouses. In AGV picking systems, AGVs transport the entire shelves including the required items (inventory shelves) or shipping boxes (sorting shelves) to the pickers instead of the pickers moving to the shelves, which improves the productivity of the picking activity in warehouses. In conventional systems, the sorting shelves are fixed or are transported only after the completion of the sorting work of the shelves. Our new system transports the sorting shelf even if the sorting shelf is in the middle of sorting. This system improves the productivity of picking activity by transporting both the shelves to appropriate locations at the appropriate time. To handle complex transport tasks, the proposed system requires a real-time scheduling method. This study applies a real-time holonic scheduling method to resolve scheduling problems. We evaluated the productivity of the proposed system and that of the conventional method that transports sorting shelves only after finishing the sorting work. The results show that the larger the working area and the higher mixed and lower-volume the picking orders are, the more efficiently the proposed method solves scheduling problems.

Safety analysis for vehicle guidance systems with dynamic fault trees

This paper considers the design-phase safety analysis of vehicle guidance systems. The proposed approach constructs dynamic fault trees (DFTs) to model a variety of safety concepts and E/E architectures for drive automation. The fault trees can be used to evaluate various quantitative measures by means of model checking. The approach is accompanied by a large-scale evaluation: The resulting DFTs with up to 300 elements constitute larger-than-before DFTs, yet the concepts and architectures can be evaluated in a matter of minutes.

Automated Guided Vehicle System Analysis in Foam Manufacturing Plant Using Petri-net

Automated Guided Vehicle System Analysis in Foam Manufacturing Plant Using Petri-net

面向智能生产车间的自动引导车系统仿真分析

面向智能生产车间的自动引导车系统仿真分析

Using Roads for Autonomous Air Vehicle Guidance

This is a study on the development of a road following vision-based guidance system for unmanned air vehicles (UAV) in real world applications. Currently, autonomous navigation requires the use of GPS. In many applications, however, dependence on GPS is undesirable. GPS signals are weak and can be jammed easily. Also, GPS waypoints may not be up-to-date. In recent years, vision-based navigation has been gaining popularity. Vision-based guidance requires existence of visible paths or extended landmarks for air vehicles to detect and follow. Roads are the most commonly available path to follow. Moreover, the abundance of events that happen along roads make them appealing subjects of surveillance. Many road detection (single images) and road tracking (videos) algorithms have been proposed in the literature. Fast detection and tracking has been the emphasis of those intended for UAVs. Due to the complexity of road detection, we not only need advanced software but also the most effective sensors. In this paper, we propose a road following algorithm that uses both RGB camera and hyperspectral sensor and report the results of actual test flights conducted in different locations and different seasons.

Influence of the Ladder-Slit Secondary on Reducing the Edge Effect and Transverse Forces in the Linear Induction Motor

Electromagnetic characteristics of single-sided linear induction motors (SLIMs) will be changed when the primary is displaced sideways from the symmetrical position in the metro. The transverse force will be produced, and edge effect will increase. In order to reduce the influence of the transverse force on the stability of the vehicle guidance system, the construction of the ladder-slit secondary, which consists of the slit aluminum and solid back-iron plates, is proposed and analyzed. A 3-D finite-element model (FEM) of the linear induction motor with the ladder-slit secondary is developed. With the different transverse displacements, the air-gap flux density, eddy currents, and forces are calculated and compared with the linear induction motor with the flat-solid secondary. It shows that the ladder-slit secondary can reduce the transverse force and edge effect, as well as is a good method to achieve the transversal stabilization of the rail vehicle.

Analyze traffic forecast for decentralized multi agent system using I-ACO routing algorithm

Traffic congestion is a condition on road networks that may cause the vehicle to move very slow, longer trip timing changes, and vehicle queue length increase. We need accurate predictions which require accurate status information about vehicles—the fact that the vehicles are distributed over large-scale road infrastructure that makes mostly challenging one. Advanced vehicle guidance systems use real time traffic information but unfortunately can only react upon the presence of traffic. Anticipatory vehicle routing is promising approach, accounting for traffic forecast information. This concept presents an efficient decentralized approach for anticipatory vehicle routing that is particularly useful in large-scale dynamic environments with some additional techniques and experiments. The approach is based on delegate multi agent systems (MAS), i.e., an environment-centric coordination mechanism that is, in part, inspired by ant behavior. This paper mainly focus on provide the traffic forecast among the road network is very efficient to minimize the traffic.

On the evaluation of AGVS-based warehouse operation performance

An automated guided vehicle system (AGVS) is an advanced material handling system widely used in various automated systems, particularly in e-commerce warehouses. The warehouse operation performance, mainly focusing on transportation efficiency, is affected by many factors, such as traffic-control policies and warehouse layouts. Based on the digraph theory and real-time control, two effective traffic-control policies with polynomial-time complexity are proposed to avoid the collision and to solve deadlocks. To accommodate more complicated situations, different types of warehouse layouts are tested. Extensive simulations are carried out to study the effects of policies, warehouse layouts, task densities and timing of an AGV to apply for a resource on the evaluation of the AGVS-based warehouse operation performance, which provide guidelines for warehouse designers.

A Case Study on The Automated Guided Vehicle System Through Reverse Engineering

A Case Study on The Automated Guided Vehicle System Through Reverse Engineering

The PAN-Robots Project: Advanced Automated Guided Vehicle Systems for Industrial Logistics

In modern manufacturing plants, automation is widely adopted in the production phases, which leads to a high level of productivity and efficiency. However, the same level of automation is generally not achieved in logistics, typically performed by human operators and manually driven vehicles. In fact, even though automated guided vehicles (AGVs) have been used for a few decades for goods transportation in industrial environments [1], they do not yet represent a widespread solution and are typically applied only in specific scenarios.

Concept and testing of an electromagnetic homing guidance system for autonomous underwater vehicles

An effective homing guidance system with precise vehicle dynamic attitude control capability is essential for reliable docking of Autonomous Underwater Vehicles (AUV). The paper describes the bio-inspired concept and electromagnetic finite element analysis-aided design and testing of an electromagnetic homing guidance system (EMHGS) comprising of an underwater dock with 400AT of electromagnetic dipole coil excited with the 20 Hz power supply; a twin-thruster AUV equipped with a differential magnetometer system, and operable in two degrees of freedom (DOF). The vehicle hydrodynamic behavior is characterized in 2 DOFs based on the thruster action and vehicle response method, and used for the control and homing guidance of the AUV. By sensing a magnetic field strength of 190nT, the EMHGS is found to have an effective range of 7 m, and capable of effecting AUV orientation correction by measuring the bearing angle. The FEA is found to comply with the experimental observations with an accuracy of 96% is extended for higher dock magnetic field strengths, and found that an EMHGS utilizing 6000AT dock coil and magnetic field sensors of same sensitivity could have a homing guidance range of 72 m. Based on a priori magnetic map, the system is capable of computing the vehicle range and velocity, serving critical inputs for realizing effective AUV short range homing and docking.

Design of Highway Intelligent Vehicle Guidance System

Now the highway’s traffic accidents are often taken place because of the influence of fog and other inclement weather. The accidents cause a very big loss to people's life and property. Therefore, it plays an important part in all-weather real-time monitoring, analyzing and early warning effectively. In this paper, a highway intelligent vehicle guidance system is developed to avoid traffic accidents occurring in highway. The system can greatly reduce the traffic accidents caused by mass of fog. The result shows that the system has high precision and reliability.

Controller Design for Avoiding Collisions in Automated Guided Vehicle Systems via Labeled Petri Nets

As for a class of automated guided vehicle systems (AGVS) that are partially controllable and with undeterministic behavior, a method is presented to design a maximally permissive controller that avoids any collision among vehicles via labeled Petri nets. It is not sure which area a vehicle enters after it leaves one because of insufficient sensors. Furthermore, a vehicle may uncontrollably enter some areas because of insufficient activators. By modeling the former case by multiple transitions labeled by a same symbol, and the latter case by an uncontrollable transition, an AGVS is represented by a labeled Petri net that is partially controllable. The whole net is partitioned into a set of dangerous regions that are controllable such that the uncontrollable issue is addressed. A method is proposed to compute the consistent marking set for a given observed sequence. By the resultant consistent marking set, the marking of each dangerous region is computed, and can be used to design a control action t o prevent each vehicle from entering each dangerous region where there is one AGV already. As a result, the maximally permissive controller is obtained.

Automatic Simultaneous Extrinsic-Odometric Calibration for Camera-Odometry System

This paper focuses on the simultaneous extrinsic-odometric calibration of a mobile robot system equipped with odometric devices and a monocular camera. Most current approaches are based on either optimization or Gaussian filter, which depends on a manually provided initial guess. In this paper, we propose a two-step fully automatic calibration algorithm, which does not require any prior knowledge of the un-calibrated parameters. In the first step, both the odometric parameters and the extrinsic ones are estimated through a non-iterative auto initialization process. In the second step, a joint optimization problem is solved iteratively to obtain a refined calibration result. By exploiting the planar motion constraints of the landmark measurements, our auto initialization method outperforms a comparison approach in robustness against the image noise. Experiments are conducted with data sets collected from both simulation and an autonomous guided vehicle system, which validates the improvement.

Optimisation of AGVs path layout in flexible manufacturing system using 0-1 linear integer programming

The use of AGVs has grown enormously since their introduction. The number of areas of application and variation in types has increased significantly. Flow path design is an important factor in the design of automated guided vehicle systems (AGVS). In this paper, problem of optimal flow path layout design of automated guided vehicles in the flexible manufacturing system is discussed. The problem is analysed and formulated as 0–1 linear integer programming model with the objective of minimising the total distance travelled by individual loaded AGV. An illustrative example of a layout consisting of four manufacturing cells with 16 nodes and 19 arcs is discussed to demonstrate the approach. In this approach only the movement of loaded vehicles with the unidirectional flow is considered. A general linear optimisation computer software package, named LINGO 14 is used to find out the optimal flow path for the layout.