This research introduces a path planning method based on the geometric A-star algorithm. The whole approach is applied to an Automated Guided Vehicle (AGV) in order to avoid the problems of many ...nodes, long-distance and large turning angle, and these problems usually exist in the sawtooth and cross paths produced by the traditional A-star algorithm. First, a grid method models a port environment. Second, the nodes in the close-list are filtered by the functions <inline-formula> <tex-math notation="LaTeX">P\left ({{x,y} }\right) </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">W\left ({{x,y} }\right) </tex-math></inline-formula> and the nodes that do not meet the requirements are removed to avoid the generation of irregular paths. Simultaneously, to enhance the stability of the AGV regarding turning paths, the polyline at the turning path is replaced by a cubic B-spline curve. The path planning experimental results applied to different scenarios and different specifications showed that compared with other seven different algorithms, the geometric A-star algorithm reduces the number of nodes by 10% ~ 40%, while the number of turns is reduced by 25%, the turning angle is reduced by 33.3%, and the total distance is reduced by 25.5%. Overall, the simulation results of the path planning confirmed the effectiveness of the geometric A-star algorithm.
This paper proposes a modular on-road wireless power transfer system with interoperable power adjustment mechanism. The paper is anticipated to enhance the capability of on-road charging during the ...movement of automated guided vehicles (AGV), by which the traveling mileage is increased, while the battery volume is decreased. The system design includes an interoperable power adjustment technique based on the detected impedance, and the moving position of AGV can be, hence, comprehended so as to facilitate the adjustment of the output power from each transmission module in a more flexible way. Through the investigation of on-road charging efficiency, all of coil magnetic analysis, misalignment charging evaluation, system stress simulation, and resonant characteristics investigation are performed. Experimental results gained from software simulation and hardware realization are beneficial for AGV charging applications.
Intelligent factory automation systems strongly rely on industrial wireless control networks which have to ensure timely and reliable data exchange among their components. This paper presents a ...comprehensive survey on recently approved International Electrotechnical Commission standard Wireless networks for Industrial Automation-Factory Automation (WIA-FA). This paper first introduces the system architecture of WIA-FA including network device, network topology, and system management, and then illustrates WIA-FA protocol stack and key technologies. Furthermore, two WIA-FA testbeds are described to demonstrate the high performance of WIA-FA. After that, three examples of practical applications are provided in this paper. One application deploys a WIA-FA network to monitor and control industrial robots in a digital workshop. The second application adopts the deployment of WIA-FA as a real-time wireless network that connects automated guided vehicles (AGVs) in a logistic sorting system. The last application coordinates multiple cooperative AGVs via the WIA-FA network to carry large and complex components. Finally, the open issues and future directions for WIA-FA networks are presented.
In recent years, green manufacturing has attracted wide attention from researchers. However, the energy efficiency problem in matrix manufacturing workshops is still a blank area. This paper ...considers a novel automatic guided vehicle (AGV) energy-efficient scheduling problem with release time (AGVEESR) to optimize the three objectives of energy consumption, number of AGVs used and customer satisfaction simultaneously. Considering the development of the AGVEESR, we extract problem-specific knowledge, establish a multiobjective mathematical model, and design a hybrid constructive heuristic. Due to the complexity of the problem, we propose an efficient multiobjective greedy algorithm (MOGA) with effective strategies such as new population initialization, greedy operation, and self-adaptive multiple neighbourhood local search. Meanwhile, an ideal-point-based construction operator in the greedy operation phase is presented to lower the computational complexity. Simulation results show that the proposed MOGA has a tremendously superior performance to the five state-of-the-art algorithms in solving the problem considered.
Recent trends towards larger and more complex systems necessitate the use of heterogeneous and flexible automated guided vehicles (AGVs) to fulfill the transport demand within a factory. To operate ...the fleet of AGVs efficiently, it is also important to consider their limited battery capacity. In this context, we tackle the problem of scheduling transport requests on multi-load and multi-ability AGVs with battery management. Each AGV can carry more than one load at a time and have specific capabilities such as lift loads, tow loads, or handle loads with a mounted robot arm. Each request consists of a pickup and a delivery task associated with an origin, a destination, a soft time window, and a priority. Each transport request may also require different AGV capabilities, and the AGV batteries can be recharged partially under consideration of a critical battery threshold. The decisions involve assigning transport and charging requests to AGVs, sequencing these requests, and determining the arrival times and charging duration. A mixed-integer linear programming model is formulated. A hybrid adaptive large neighborhood search with an integrated local search method is proposed to find a feasible schedule with the aim to minimize the tardiness costs of requests and travel costs of AGVs. We illustrate the efficacy of the hybrid algorithm with an industry case study using real-world data. The computational results reveal a 20%–50% cost reduction in current practice by using our hybrid algorithm, and around 50% cost reduction with respect to a single-load AGV scheduling approach proposed in the literature.
•We study the scheduling of heterogeneous multi-load AGVs with battery constraints.•We propose a hybrid algorithm based on adaptive large neighborhood search.•We provide data for an industry case study used in the numerical experiments.•The algorithm yields about 20%–50% cost reduction with respect to current practice.
Issue Title: Special Issue: Recent Advances on Control and Architectural Design of Robotic Systems Automated guided vehicles (AGVs) are used as a material handling device in flexible manufacturing ...systems. Traditionally, AGVs were mostly used at manufacturing systems, but currently other applications of AGVs are extensively developed in other areas, such as warehouses, container terminals and transportation systems. This paper discusses literature related to different methodologies to optimize AGV systems for the two significant problems of scheduling and routing at manufacturing, distribution, transshipment and transportation systems. We categorized the methodologies into mathematical methods (exact and heuristics), simulation studies, meta-heuristic techniques and artificial intelligent based approaches.
•Path planning in large dense grid-based automated guided vehicle systems.•Proposal and simulation of a real-time dynamic path planning approach.•Using a graph-based system representation with ...changing vertex weights over time.•Enabling deadlock recovery through re-planning over time.•Evaluation through discrete event simulations on four layouts for two AGV densities.
Real-time path planning for large, dense grid-based automated guided vehicle (AGV) systems, used for example to sort parcels, is challenging. Most approaches described in the literature are not fast enough for real-time control or are not able to avoid congestion. This paper presents a dynamic approach using a graph-representation of the grid system layout with vertex weights that are updated over time. By means of an extensive discrete-event simulation, we show that the proposed path planning approach significantly increases the throughput compared to existing approaches. Furthermore, it enables the recovery from deadlock situations.
In this paper, decentralized motion planning and scheduling of automated guided vehicles (AGVs) in a flexible manufacturing system is proposed. A motion planner is combined with a scheduler allowing ...each AGV to update its destination resource during navigation in order to complete the transported product. The proposed strategy is based on two steps. The first step consists in planning a presumed trajectory to avoid collision conflicts previously detected by a central supervisor, enabling more appropriate decentralized scheduling by AGVs. The presumed trajectories, which represent the intentions of AGVs, are then exchanged with neighboring AGVs. The second step uses the presumed trajectories of neighbors to compute a collision-free trajectory according to the priority policy. Numerical and experimental results are provided to show the pertinence and the feasibility of the proposed strategy.
•Multi-load AGV systems are simulated using Coloured Petri nets.•The impact of failure of multi-load AGVs on system performance is investigated.•Major factors that need to be considered in the design ...of AGV systems are studied.•The impacts of various maintenance strategies on system performance are discussed.•Combined use of periodic maintenance and backup AGV can replace onsite maintenance.
Multi-load Automated Guided Vehicle's (AGV) are regarded as a potential tool to tackle the low-efficiency issue that have plagued traditional single-load AGV systems for many years. However, to date, the optimal design and operation of multi-load AGV systems is still an unresolved question. In order to explore the answer to this question and help operators make decisions during the design and operation of these systems, this article will use Coloured Petri nets (CPN) to develop a mathematical model to investigate the performance (i.e., the total number of items delivered within a given time) of the multi-load AGV system in various scenarios. The research has shown that the failure of multi-load AGVs can significantly lower the performance of the AGV system. Although it is possible to maintain high system performance by performing onsite corrective maintenance, the research shows that this can be achieved using a combination of periodic maintenance and backup AGV use. Finally, it is found that increasing the number of multi-load AGVs can increase system performance, but will decrease the efficiency (i.e., the average number of items delivered per AGV) of the individual AGVs in the system due to the increased traffic conflicts and hence longer waiting times.
•A deep reinforcement learning based real-time scheduling for Automated Guided Vehicles is proposed.•Useful policy can be achieved through continuous training process.•Adaptive and efficient ...decisions can be made based on the proposed approach.
Driven by the recent advances in industry 4.0 and industrial artificial intelligence, Automated Guided Vehicles (AGVs) has been widely used in flexible shop floor for material handling. However, great challenges aroused by the high dynamics, complexity, and uncertainty of the shop floor environment still exists on AGVs real-time scheduling. To address these challenges, an adaptive deep reinforcement learning (DRL) based AGVs real-time scheduling approach with mixed rule is proposed to the flexible shop floor to minimize the makespan and delay ratio. Firstly, the problem of AGVs real-time scheduling is formulated as a Markov Decision Process (MDP) in which state representation, action representation, reward function, and optimal mixed rule policy, are described in detail. Then a novel deep q-network (DQN) method is further developed to achieve the optimal mixed rule policy with which the suitable dispatching rules and AGVs can be selected to execute the scheduling towards various states. Finally, the case study based on a real-world flexible shop floor is illustrated and the results validate the feasibility and effectiveness of the proposed approach.
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