Recent progress in the field of robotic manipulation has generated interest in fully automatic object packing in warehouses. This article presents a formulation of the robotic packing problem that ...ensures stability of the object pile during packing and the feasibility of the robot motion while maximizing packing density. A constructive packing algorithm is proposed to address this problem by searching over the space of item positions and orientations. Moreover, a new heightmap minimization heuristic is shown to outperform existing heuristics in the literature in the presence of nonconvex objects. Two strategies for improving the robustness of executed packing plans are also proposed: 1) conservative planning ensures plan feasibility under uncertainty in model parameters; and 2) closed-loop packing uses vision sensors to measure placement errors and replans to correct for them. The proposed planner and error mitigation strategies are evaluated in simulation and on a state-of-the-art physical packing testbed. Experiments demonstrate that the proposed planner generates high-quality packing plans, and the error mitigation strategies improve success rates beyond an open-loop baseline from 83% to 100% on five-item orders.
Warehouse/distribution center (DC) automation technology for the retail industry promises to reduce operational costs, improve flexibility and response time for customers, and help improve network ...productivity, thus making it very relevant for omni/multichannel (OC/MC) settings. However, the investment required to acquire the DC automation technology is high, and hence, the investment decision must be operationally and financially comprehensive. In fact, an automated DC has a network-wide impact: it can benefit players in the network, but in turn is exposed to network risks and the investment must be safeguarded. While the need for a comprehensive decision-making framework and safeguarding strategy is stressed by scholars, such a framework is lacking. Further, corresponding integrated sub-frameworks for key elements in the OC/MC value chain are also missing. In this paper, we address these gaps and contribute by providing a) generalized and integrated three-part framework, b) corresponding sub-frameworks, c) discrete event, economic, and math programming models, d) rapid-sizing/analysis tools based on: i) analysis at the DC-level, ii) network level, iii) economic/business level, and iv) contract level (sustainable supplier/distribution relationship). In this reference, we investigate a new generation ‘full-case’ technology that has been recognized as a key to warehouse automation. The insights from our research inform several strategic tradeoffs (extent of automation, investment in labor vs. capital, response vs. efficiency, and sustainable supplier management) relevant for decision-making and safeguarding an expensive asset such as an automated DC. Our analysis is based on interviews (retailers, automated and conventional DCs, and DC equipment suppliers), on-site observations, secondary data, and learning from analytical models. We also present an illustrative real-life application/case study of the framework and the modeling details in the E-component.
•Present integrative framework (OC/ MC setting) for investment decision-making for DC, considering degree of automation•While we focus on ‘full case’ technology, our work has general appeal.•Three sub-frameworks include i) DC sizing ii) Network analysis ii) Economic analysis; rapid-sizing provided in E-component•We identify four levels of analysis: i) strategic, ii) supply/distribution chain, iii) DC, iv) store.•We validate our work through: a) organizations in item 5 above, b) conferences and c) trade publications.
Online 3D Bin Packing Problem (3D-BPP) has a wide range of industrial applications and there is an emerging research interest in learning optimal bin packing policy and deploying it for real ...logistics applications. From the heuristic methods to the deep reinforcement learning (DRL) methods, the previous works have proposed many solutions to solve the online 3D-BPP. However, none of them have studied what and how heuristics can be modelled into DRL to build a more effective and practical bin packing pipeline. In this work, we thoroughly investigate what heuristics can be used in online 3D-BPP and how to effectively integrate the heuristics with the DRL. First, we design 3 different heuristics based on the physical rules of the real world and the experiences of the human packers, including the Physics-Heuristics, the Packing-Heuristics and the Unpacking-Heuristics. Second, we model the 3 types of heuristics into the DRL framework and propose a novel heuristic DRL method to solve the online 3D-BPP. Extensive experimental results show that our method achieves state-of-the-art bin packing performance and the resulting real-world system is able to reliably finish the bin packing task in real logistics scenarios. Supplementary video is available at https://www.youtube.com/watch?v=x8GpmEELq18. Note to Practitioners -The rapid growth of e-commerce has significantly increased the burden of human packers in logistic warehouses, where the workers need to pick the products from a conveyor and pack them into bins (i.e. the online 3D bin packing). Thus it is of great importance to develop intelligent robotic systems to replace human labor, which is a long-standing topic in the field of control and automation science. This paper makes a substantial contribution to the related field by studying the online 3D bin packing in terms of both the theory and practice. On the one hand, the simulated experiments suggest that the presented algorithm significantly improves the space utilization of bin packing. On the other hand, the robotic system developed based on the proposed method can favourably finish the bin packing task in real logistics scenarios, demonstrating the practical use of our approach. Consequently, the approach proposed in this paper is totally applicable in logistic warehouses and is promising to drastically improve the working efficiency of the product packing in real warehouses. In the future, we will extend the presented approach to pack irregular-shaped objects and then facilitate more logistics applications.
Pallet racking is an essential element within warehouses, distribution centers, and manufacturing facilities. To guarantee its safe operation as well as stock protection and personnel safety, pallet ...racking requires continuous inspections and timely maintenance in the case of damage being discovered. Conventionally, a rack inspection is a manual quality inspection process completed by certified inspectors. The manual process results in operational down-time as well as inspection and certification costs and undiscovered damage due to human error. Inspired by the trend toward smart industrial operations, we present a computer vision-based autonomous rack inspection framework centered around YOLOv7 architecture. Additionally, we propose a domain variance modeling mechanism for addressing the issue of data scarcity through the generation of representative data samples. Our proposed framework achieved a mean average precision of 91.1%.
The recent development of an omnichannel business environment provides a seamless shopping experience throughout the customer journey. Although previous studies have identified the importance of ...rapid product delivery, consumers cannot evaluate delivery quality until it has arrived. This study argued that warehouse automation and retail channel brand characteristics lead to informative signals and to firms' higher sales in the omnichannel context. By analyzing panel data from the Japanese retail market, we tested the effects of warehouse automation and the moderating effects of omnichannel, online, and offline brand offerings on the effectiveness of the warehouse automation signal. Results showed that warehouse automation signaling positively affects firms’ sales and has a positive interaction effect with omnichannel offerings.
•The information of warehouse automation implementation leads to higher sales.•The presence of information about warehouse automation implementation by third-party sources (e.g., newspapers) positively affects sales.•This study offers a conceptual interpretation based on the consumer's signal inference.
In this paper we present an online supervisory control approach, based on limited lookahead policy, that is amenable for the control of multi-agent discrete-event systems. We then apply this online ...control scheme to model and control a warehouse automation system served by multiple mobile robots; the effectiveness of this scheme is demonstrated through a case study. Moreover, we build an experiment testbed for testing the validity of our proposed method with implementation on real robots.
•A novel modification to the existing online supervisory control for multi-agent DES.•Demonstration of a warehouse automation system served by multiple robots.•An experiment testbed consisting of multiple LEGO robots.
As e-commerce has become more prevalent, the required logistics operations are challenged by the greater demand for and higher complexity of order picking in warehouses. While goods-to-person (G2P) ...picking systems, such as robotic mobile fulfillment systems, are becoming popular, there are still challenges in G2P systems, including the unstable performance of human picking due to fatigue and human errors, and the constrained mobility of robots. To tackle these challenges, this article presents a new robotic storage and order picking system, which we call RubikCell. It leverages the strengths of existing warehouse systems and incorporates automatic dispensing, robot-to-goods picking, and pick-while-sort operations. In RubikCell, robots are equipped with trays to store and transport items for an order, instead of moving with heavy pods to workstations as in G2P systems. In addition, the concept of cellular warehousing (CW)-inspired by cellular manufacturing-aims to operate a large warehouse with smaller warehousing cells. This approach reduces the substantial traveling distances of robots, as they move within their dedicated warehousing cells rather than the entire warehouse. A mathematical programming model is developed to address the cell formation problem in CW. Lastly, the implementation of CW principles in RubikCell, forming Robotic CW Systems, renders e-commerce warehousing more flexible, scalable, and reconfigurable. Numerical experiments conducted on this innovative system have confirmed the effectiveness of the cell formation method.
The goal of this work is to develop the next generation of coordinated optimal planning and control schemes for real-world robotic applications, with cost-effective intelligent robots that can safely ...and robustly perform the tasks at hand. This article presents a dual-loop optimal hierarchical control scheme for robotic manipulators consisting of outer and inner loops. The outer kinematic control loop in the operational space provides a joint velocity reference signal to the inner one. The kinematic control is formulated as a closed-loop optimal control approach to trajectory generation where the desired target (possibly time-varying) is obtained by acting upon the feedback from the actual state of the robot. The kinematic control is obtained using a closed-form analytic solution of the Hamilton-Jacobi-Bellman (HJB) equation. The proposed methodology defines the task in terms of the integral cost function, which results in a global optimal solution. The inner dynamic control loop consists of a neural network (NN)-based adaptive critic (AC) optimal tracking control scheme. The online NN approximator-based dynamic controller learns the infinite-horizon cost function related to inner loop error dynamics in continuous time and calculates the corresponding optimal control input to minimize the cost function forward in time. The stability and the performance of the proposed control scheme are shown theoretically via the Lyapunov approach and also verified experimentally using a 7-DOF Barrett WAM robot manipulator. The warehousing applications of the proposed dual-loop control scheme have been demonstrated experimentally in an exact warehouse setting. Note to Practitioners -This article was motivated by our previous experiences in the Amazon Robotics Challenge (ARC) competitions as a participant. Although the major lessons from those events revealed many important issues toward warehouse automation both from robotic vision and grasping aspects, the application aspects of control engineering to solution for these real-world problems could significantly benefit the today's highly automated society. The intention of this article is to address this situation by designing a cost-effective robot manipulator control scheme by optimizing robot manipulation trajectories in the outer loop along with the actuator input in the inner loop. Therefore, we propose a dual-loop optimal control scheme for robotic manipulations under a cost-optimal framework with guaranteed stability proof via the Lyapunov approach. This results in smoother trajectories with cost-effective control actuator inputs than the state-of-the-art methods. We believe that this work can be beneficial for academic and industrial research to design more advanced and optimized solutions in this domain.
A robotic mobile fulfillment system (RMFS) performs the order fulfillment process by bringing inventory to workers at pick-pack-and-ship warehouses. In the RMFS, robots lift and carry shelving units, ...called inventory pods, from storage locations to picking stations where workers pick items off the pods and put them into shipping cartons. The robots then return the pods to the storage area and transport other pods. In this article, we consider an item assignment problem in the RMFS in order to maximize the sum of similarity values of items in each pod. We especially focus on a reoptimization heuristic to address the situation where the similarity values are altered so that a good assignment solution can be obtained quickly with the changed similarity values. A constructive heuristic algorithm for the item assignment problem is developed, and then, a reoptimization heuristic is proposed based on the constructive heuristic algorithm. Then, computational results for several instances of the problem with 10-500 items are presented. We further analyze the case for which an item type can be placed into two pods. Note to Practitioners -This article proposes an efficient heuristic algorithm for assigning items to pods in a robotic mobile fulfillment system (RMFS) so that items ordered together frequently are put into the same pod. Computational results with 10-500 items show that the gaps from upper bounds are very small on average. For cases where the similarity values between items change or their estimation is not accurate due to the fluctuations in demand, a reoptimization heuristic algorithm that alters the original assignment is developed. The experimental results show that the reoptimization algorithm is robust when perturbation levels are approximately 40%-50% of the original similarity values with much less computation times. We believe that this research work can be very helpful for operating the RMFS efficiently.
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