Automated Guided Vehicles(AGVs)have been introduced into various applications,such as automated warehouse systems,flexible manufacturing systems,and container terminal systems.However,few publications have outlined pr...Automated Guided Vehicles(AGVs)have been introduced into various applications,such as automated warehouse systems,flexible manufacturing systems,and container terminal systems.However,few publications have outlined problems in need of attention in AGV applications comprehensively.In this paper,several key issues and essential models are presented.First,the advantages and disadvantages of centralized and decentralized AGVs systems were compared;second,warehouse layout and operation optimization were introduced,including some omitted areas,such as AGVs fleet size and electrical energy management;third,AGVs scheduling algorithms in chessboardlike environments were analyzed;fourth,the classical route-planning algorithms for single AGV and multiple AGVs were presented,and some Artificial Intelligence(AI)-based decision-making algorithms were reviewed.Furthermore,a novel idea for accelerating route planning by combining Reinforcement Learning(RL)andDijkstra’s algorithm was presented,and a novel idea of the multi-AGV route-planning method of combining dynamic programming and Monte-Carlo tree search was proposed to reduce the energy cost of systems.展开更多
With the wide application of automated guided vehicles(AGVs) in large scale outdoor scenarios with complex terrain,the collaborative work of a large number of AGVs becomes the main trend.The effective multi-agent path...With the wide application of automated guided vehicles(AGVs) in large scale outdoor scenarios with complex terrain,the collaborative work of a large number of AGVs becomes the main trend.The effective multi-agent path finding(MAPF) algorithm is urgently needed to ensure the efficiency and realizability of the whole system. The complex terrain of outdoor scenarios is fully considered by using different values of passage cost to quantify different terrain types. The objective of the MAPF problem is to minimize the cost of passage while the Manhattan distance of paths and the time of passage are also evaluated for a comprehensive comparison. The pre-path-planning and real-time-conflict based greedy(PRG) algorithm is proposed as the solution. Simulation is conducted and the proposed PRG algorithm is compared with waiting-stop A^(*) and conflict based search(CBS) algorithms. Results show that the PRG algorithm outperforms the waiting-stop A^(*) algorithm in all three performance indicators,and it is more applicable than the CBS algorithm when a large number of AGVs are working collaboratively with frequent collisions.展开更多
The position control problem of differential-driven automated guided vehicles(AGVs)based on the prescribed-time control method is studied.First,an innovative orientation error function is proposed by an auxiliary arcs...The position control problem of differential-driven automated guided vehicles(AGVs)based on the prescribed-time control method is studied.First,an innovative orientation error function is proposed by an auxiliary arcsine function about the orientation angle.Thus,the problem of position control of AGV is transformed into the stabilisation control of the kinematic system.Second,by introducing a reserved time parameter and a smooth switching function,a novel time-varying scaling function is proposed.This novel scaling function avoids the risk of infinite gain in the conventional prescribed-time control method while ensuring the smoothness of control laws.Then,an improved velocity constraint function is proposed using the Gaussian function.Compared with the existing constraint function,the proposed method not only has more smoothness but also solves the balance point errors caused by the large AGV orientation errors.The presented method ensures that the AGV reaches the target position in a prescribed time.Hence,the upper bound of the AGV system state can be determined by adjusting parameters.Matlab simulation results show that the proposed controller can effectively make the AGV system state satisfy the prescribed bound.展开更多
The traditional automated guided vehicle(AGV) on goods delivery faces the challenges when task space expands beyond 2 D plans. 3 D environments such as uneven terrain, ramps, and staircase are typical in construction ...The traditional automated guided vehicle(AGV) on goods delivery faces the challenges when task space expands beyond 2 D plans. 3 D environments such as uneven terrain, ramps, and staircase are typical in construction site. Thus, the key to introducing this technology into construction industry is to improve AGV’s stability and autonomous navigation ability in more complex three-dimensional environments. In this paper, mobileman, a novel tracked autonomous guide vehicle, is introduced. Compared with other construction robots, mobileman maximizes its load capacity on the basis of assuring accessibility. Furthermore, its modular designs and self-balancing platform enable it to cope with more complex challenging scenarios, such as staircase with 35-degree sloped staircase, while another modular design featured automated loading and unloading functionality. The mobile base specifications were presented in section two, and modular designs and exploration of the navigation system on construction site were illustrated in the rest of sections.展开更多
We present an extension of the resource-constrained multi-product scheduling problem for an automated guided vehicle(AGV) served flow shop, where multiple material handling transport modes provide movement of work pie...We present an extension of the resource-constrained multi-product scheduling problem for an automated guided vehicle(AGV) served flow shop, where multiple material handling transport modes provide movement of work pieces between machining centers in the multimodal transportation network(MTN). The multimodal processes behind the multi-product production flow executed in an MTN can be seen as processes realized by using various local periodically functioning processes. The considered network of repetitively acting local transportation modes encompassing MTN's structure provides a framework for multimodal processes scheduling treated in terms of optimization of the AGVs fleet scheduling problem subject to fuzzy operation time constraints. In the considered case, both production takt and operation execution time are described by imprecise data. The aim of the paper is to present a constraint propagation(CP) driven approach to multi-robot task allocation providing a prompt service to a set of routine queries stated in both direct and reverse way. Illustrative examples taking into account an uncertain specification of robots and workers operation time are provided.展开更多
文摘Automated Guided Vehicles(AGVs)have been introduced into various applications,such as automated warehouse systems,flexible manufacturing systems,and container terminal systems.However,few publications have outlined problems in need of attention in AGV applications comprehensively.In this paper,several key issues and essential models are presented.First,the advantages and disadvantages of centralized and decentralized AGVs systems were compared;second,warehouse layout and operation optimization were introduced,including some omitted areas,such as AGVs fleet size and electrical energy management;third,AGVs scheduling algorithms in chessboardlike environments were analyzed;fourth,the classical route-planning algorithms for single AGV and multiple AGVs were presented,and some Artificial Intelligence(AI)-based decision-making algorithms were reviewed.Furthermore,a novel idea for accelerating route planning by combining Reinforcement Learning(RL)andDijkstra’s algorithm was presented,and a novel idea of the multi-AGV route-planning method of combining dynamic programming and Monte-Carlo tree search was proposed to reduce the energy cost of systems.
基金Supported by the National Key Research and Development Program of China(No.2020YFC1807904).
文摘With the wide application of automated guided vehicles(AGVs) in large scale outdoor scenarios with complex terrain,the collaborative work of a large number of AGVs becomes the main trend.The effective multi-agent path finding(MAPF) algorithm is urgently needed to ensure the efficiency and realizability of the whole system. The complex terrain of outdoor scenarios is fully considered by using different values of passage cost to quantify different terrain types. The objective of the MAPF problem is to minimize the cost of passage while the Manhattan distance of paths and the time of passage are also evaluated for a comprehensive comparison. The pre-path-planning and real-time-conflict based greedy(PRG) algorithm is proposed as the solution. Simulation is conducted and the proposed PRG algorithm is compared with waiting-stop A^(*) and conflict based search(CBS) algorithms. Results show that the PRG algorithm outperforms the waiting-stop A^(*) algorithm in all three performance indicators,and it is more applicable than the CBS algorithm when a large number of AGVs are working collaboratively with frequent collisions.
基金supported by the Scientific Research Fund of the Zhejiang Provincial Education Department under Grants No.Y202146005 and No.Y202248462the General Scientific Project of Huzhou University under Grant No.2021XJKJ04+1 种基金the Huzhou University Scientific Research Innovation Project under Grant No.2022KYCX58,the Zhejiang Province New Young Talent Plan Project in 2022 under Grant No.2022R431B021the Zhejiang Provincial Education Department General Research Project in 2022 under Grant No.Y202250212.
文摘The position control problem of differential-driven automated guided vehicles(AGVs)based on the prescribed-time control method is studied.First,an innovative orientation error function is proposed by an auxiliary arcsine function about the orientation angle.Thus,the problem of position control of AGV is transformed into the stabilisation control of the kinematic system.Second,by introducing a reserved time parameter and a smooth switching function,a novel time-varying scaling function is proposed.This novel scaling function avoids the risk of infinite gain in the conventional prescribed-time control method while ensuring the smoothness of control laws.Then,an improved velocity constraint function is proposed using the Gaussian function.Compared with the existing constraint function,the proposed method not only has more smoothness but also solves the balance point errors caused by the large AGV orientation errors.The presented method ensures that the AGV reaches the target position in a prescribed time.Hence,the upper bound of the AGV system state can be determined by adjusting parameters.Matlab simulation results show that the proposed controller can effectively make the AGV system state satisfy the prescribed bound.
文摘The traditional automated guided vehicle(AGV) on goods delivery faces the challenges when task space expands beyond 2 D plans. 3 D environments such as uneven terrain, ramps, and staircase are typical in construction site. Thus, the key to introducing this technology into construction industry is to improve AGV’s stability and autonomous navigation ability in more complex three-dimensional environments. In this paper, mobileman, a novel tracked autonomous guide vehicle, is introduced. Compared with other construction robots, mobileman maximizes its load capacity on the basis of assuring accessibility. Furthermore, its modular designs and self-balancing platform enable it to cope with more complex challenging scenarios, such as staircase with 35-degree sloped staircase, while another modular design featured automated loading and unloading functionality. The mobile base specifications were presented in section two, and modular designs and exploration of the navigation system on construction site were illustrated in the rest of sections.
文摘We present an extension of the resource-constrained multi-product scheduling problem for an automated guided vehicle(AGV) served flow shop, where multiple material handling transport modes provide movement of work pieces between machining centers in the multimodal transportation network(MTN). The multimodal processes behind the multi-product production flow executed in an MTN can be seen as processes realized by using various local periodically functioning processes. The considered network of repetitively acting local transportation modes encompassing MTN's structure provides a framework for multimodal processes scheduling treated in terms of optimization of the AGVs fleet scheduling problem subject to fuzzy operation time constraints. In the considered case, both production takt and operation execution time are described by imprecise data. The aim of the paper is to present a constraint propagation(CP) driven approach to multi-robot task allocation providing a prompt service to a set of routine queries stated in both direct and reverse way. Illustrative examples taking into account an uncertain specification of robots and workers operation time are provided.
