The logistics market has been impacted by increase of e-commerce, mass customization, omni-channel distribution, and just-in-time philosophy. In order to attend to this dynamic change, automation has been applied in warehouses. Although, some researches point out the lack of flexibility as a bottleneck. Therefore, a comprehensive literature review of recent papers is vital to draw a framework of the past and to shed light on future directions. This paper aims to review published papers in the last ten years related to flexible automation in warehouses and to construct a framework that could guide future researchers in the construction of an innovative conceptual model that may be applied at warehouses in the future. A total of 113 papers published between January 2008 and December 2018 have been selected, reviewed, and categorized to construct a useful foundation of past research. Results showed the key point to achieve a flexible automated warehouse is the combination of automated equipment, data collection technologies, and management solutions. Finally, based on the reviewed papers, an innovative framework of a flexible automated warehouse is proposed.

Flexible automated warehouse: a literature review and an innovative framework

This paper contributes to a taxonomy of augmented reality and robotics based on a survey of 460 research papers. Augmented and mixed reality (AR/MR) have emerged as a new way to enhance human-robot interaction (HRI) and robotic interfaces (e.g., actuated and shape-changing interfaces). Recently, an increasing number of studies in HCI, HRI, and robotics have demonstrated how AR enables better interactions between people and robots. However, often research remains focused on individual explorations and key design strategies, and research questions are rarely analyzed systematically. In this paper, we synthesize and categorize this research field in the following dimensions: 1) approaches to augmenting reality; 2) characteristics of robots; 3) purposes and benefits; 4) classification of presented information; 5) design components and strategies for visual augmentation; 6) interaction techniques and modalities; 7) application domains; and 8) evaluation strategies. We formulate key challenges and opportunities to guide and inform future research in AR and robotics.

Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfaces

An AR-assisted Deep Reinforcement Learning-based approach towards mutual-cognitive safe human-robot interaction

The paper presents the propagation analysis of ultrawideband Gaussian signal in an automated collaborative warehouse environment where human and robots communicate to ensure that mutual collisions do not occur. The warehouse racks are principally modeled as clusters of metallic (PEC) parallelepipeds, with dimensions chosen to approximate the realistic warehouse. The signal propagation is analyzed using a ray tracing software, with the goal to calculate the path loss profile for different representative scenarios and antenna polarizations. The influence of the rack surface roughness onto propagation is also analyzed. The guidelines for optimum antenna positions on humans and robots for safe communication are proposed according to the simulations results.

Analysis of Safe Ultrawideband Human-Robot Communication in Automated Collaborative Warehouse

Picking with a robot colleague: A systematic literature review and evaluation of technology acceptance in human-robot collaborative warehouses

Nowadays, production systems and warehouses still lack human-robot collaboration. Often due to safety issues robots are kept behind safety fences and the overall system is shutdown once a human enters. This paper is based on a new concept to overcome these issues. It consists of a safety concept which ensures a more efficient human-robot collaboration. The human worker can be localized via a safety vest which he/she wears and the nearby robots are also aware of this information. We propose a more efficient and safe overall system by using an Augmented Reality device which offers a simple interface between humans and robots and a Heterogeneous Fleet Management System which plans and provides collision-free paths for humans and robots and ensures that the resulting environment is safe for both robots and humans.

Safe Human-Robot-Interaction in Highly Flexible Warehouses using Augmented Reality and Heterogenous Fleet Management System

This paper addresses the problem of mapping and localization for optically guided Automated Guided Vehicles (AGV) that are widely needed in the warehousing industry. It describes an approach to build a floor plan of the optical path traversed by the AGV, while keeping the process cost-effective by using the AGVs internal sensors and the optical sensor used to keep track of the path. The idea is to create a distributed system where each AGV knows its location in the warehouse and is capable of calculating an optimal path when given a destination without having to map the environment prior. This is done through fusion of maps from multiple AGV. Each AGV creates its own map and communicates it to the mapping module which collects maps from all the AGV in the system and creates a fused map. Such a map needs to be robust against errors and noise from multiple AGV.

Preity Gupta

Papers

Safe Human-Robot-Interaction in Highly Flexible Warehouses using Augmented Reality and Heterogenous Fleet Management System

Multi-Robot Mapping for Optically Guided Vehicles