Autonomous mobile robot travel under deadlock and collision prevention algorithms by agent-based modelling in warehouses

Recent dramatic increase in e-commerce has also increased the adoption of automation technologies in warehouses. Autonomous mobile robots (AMRs) are from those technologies widely utilized in warehouse operations. It is important to design the operation of those robotic systems in such a way that, they meet the current and future system requirements correctly. In this paper, we study flexible travel of AMRs in warehouses by developing smart deadlock and collision prevention algorithms on agent-based modelling. By that, AMR agents can interact with each other and environment, so that they can make smart decisions maximizing their goals. We compare the performance of the developed flexible travel system with non-flexible designs where there is a single AMR dedicated to a specific zone so that no deadlock or collision possibility takes place. The results show that AMRs may provide up to 39% improvement in the flexible system compared to its non-flexible design

Intelligent Autonomous Vehicles in digital supply chains: A framework for integrating innovations towards sustainable value networks

The principal objective of this research is to provide a framework that captures the main software architecture elements for developing highly customized simulation tools that support the effective integration of Intelligent Autonomous Vehicles (IAVs) in sustainable supply networks, as an emerging field in the operations management agenda. To that end, the study's contribution is fourfold including: (i) a review of software simulation tools and platforms used in assessing the performance of IAVs interlinked with sustainability ramifications in supply chain (SC) ecosystems, (ii) an integrated software framework for monitoring and assessing the sustainability performance of SCs defined by the utilisation of innovative IAVs in operations, (iii) a translation of the proposed SC framework into a corresponding software application through a robust five-stage stepwise process, and (iv) a demonstration of the developed software tool through its application on the case of an IAV system operating in a customisable warehouse model. Our analysis highlights the flexibility resulting from a decentralised software management architecture, thus enabling the dynamic reconfiguration of a SC network. In addition, the developed pilot simulation tool can assist operations managers in capturing the operational needs of facilities and assessing the performance of IAV systems while considering sustainability parameters

Contemporary Robotics

This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials

Satellite Services Workshop, volume 2

Methods for on-orbit servicing of satellites are discussed

Models and Optimal Controls for Smart Homes and their Integration into the Electric Power Grid

Smart homes can operate as a distributed energy resource (DER), when equipped with controllable high-efficiency appliances, solar photovoltaic (PV) generators, electric vehicles (EV) and energy storage systems (ESS). The high penetration of such buildings changes the typical electric power load profile, which without appropriate controls, may become a “duck curve” when the surplus PV generation is high, or a “dragon curve” when the EV charging load is high. A smart home may contribute to an optimal solution of such problems through the energy storage capacity, provided by its by battery energy storage system (BESS), heating, ventilation, and air conditioning (HVAC) system, and electric water heater (EWH), and the advanced controls of an home energy management (HEM). The integrated modeling of home energy usage and electric power distribution system, developed as part of this dissertation research, provides a testbed for HEM control methods and prediction of long-term scenarios. A hybrid energy storage system including batteries and a variable power EWH was proposed. It was demonstrated that when the operation of the proposed hybrid energy storage system was coordinated with PV generation, the required battery capacity would be substantially reduced while still maintaining the same functionality for smart homes to operate as dispatchable generators. A newly developed co-simulation framework, INSPIRE+D, enables the dynamic simulation of smart homes and their connection to the grid. The equivalent thermal model of a reference house was proposed with parameters based on the systematic study of experimental data from fully instrumented field demonstrators. Energy storage capacity of HVAC systems was calculated and an equivalent state-of-charge (SOC) was defined. The aggregated HVAC load was calculated based on special HVAC parameters and a sequential DR scheme was proposed to reduce both ramping rate and peak power, while maintaining human comfort according to ASHRAE standards. A long short-term memory (LSTM) method was applied to for the identification of HVAC system from the aggregated data. The generic water heater load curves based on the data retrieved from large experimental projects for resistive EWHs and heat pump water heaters (HPWHs) were created. A community-level digital twin with scalability has been developed to capture the aggregated hot water flow and average hot temperature in the tanks. The potential electricity saving of shifting from EWH to HPWH was calculated. The energy storage capacities for both EWHs and HPWHs were calculated. Long term load prediction by considering different fractions of smart homes with HEM for at the power system was provided based on one of the largest rural field smart energy technology demonstrators located in Glasgow, KY, US. Also demonstrates was the ability of EWH to provide ancillary services while maintaining customer comfort. The minimum participation rates for EWH and batteries were calculated and compared with respect to different peak reduction targets. The aggregated charging load for EV in a community was calculated based on data from the National Travel Household Survey (NHTS). The EV charging and RESS operation were scheduled to reduce the daily utility charge. Building resilience was quantified by analyzing the self-sustainment duration for all possible power outages throughout an entire year based on the annual electricity usage of a typical California residence. The influence of factors such as energy use behavioral patterns, BESS capacity, and an availability of EV was evaluated. A concept of generalized energy storage (GES) model for BESS, EWH and HVAC systems was proposed. The analogies, including SOC versus water/indoor temperature differential, were identified and explained, and models-in-the-loop (MIL) were introduced, which were compatible with the Energy Star and Consumer Technology Association (CTA)-2045 general specifications and command types. A case study is included to illustrate that the “energy content” and “energy take” for BESS and EWH. The main original contributions of this dissertation include the comprehensive simulation of the total building energy usage and the development of the co-simulation framework incorporating building and power system simulators. Another contribution of the dissertation is the quantification of building resilience based on the building energy usage model. The dissertation also contributes to the concept of GES which regards the HVAC and EWH as virtual energy storage and their unified controls with BESS. The GES facilitates the employment of industrial standards, e.g., CTA-2045, and the hybrid ESS reduces required BESS capacity. This dissertation contributes to the modeling of aggregated load for EWH, HVAC, and EV using different methods and long term forecasting of power profile at the system level. The aggregated generic load for EWH was calculated based on large amount of field data, the aggregated EV charging load was estimated based on national survey results, and the aggregated HVAC load was simulated based on the modeling of every residences, where the model parameters were populated according to special distributions. The methods based LSTM for the identification of HVAC power from the aggregated load was developed

Otimização e Simulação de Sistemas de Logística Interna - Caso Real de Definição de Rotas Milk Run numa Empresa de Semicondutores

A melhoria da eficiência operacional depende de um vasto número de decisões, sendo a redução de custos e atrasos associados aos sistemas de manuseamento de materiais, aspetos essenciais para obter níveis superiores de produtividade. Neste contexto, a abordagem milk run procura otimizar a movimentação de materiais, através de uma melhor definição de rotas e frequências de transporte. Esta tese propõe uma abordagem híbrida de otimização e simulação, para desenhar um milk run numa empresa de semicondutores, a ser implementado através de um sistema de transporte automático de carga (AGV - Automated Guided Vehicle).O modelo de otimização procura obter soluções ótimas das rotas em termos de custo total de operação. Enquanto o modelo de simulação centra-se na avaliação detalhada de vários cenários, estimando o impacto que o milk run tem em variáveis relevantes do sistema de produção, como o lead time dos produtos, tamanho dos buffers de entrada e saída e taxa de utilização dos AGVs. Neste trabalho, foi adotada a plataforma de otimização CPLEX, que foi combinada com o avançado software de simulação SIMIO. Os resultados demonstram a importância da relação entre a otimização e simulação para obter soluções mais robustas e confiança no desenho da solução final

Diseño e implantación de una línea de AGVs

El estudio que a lo largo de este trabajo se presenta se enfoca en la modificación y puesta a punto de un circuito de vehículos de guiado automático (AGV) que se emplea para el transporte de piezas en el interior de una fábrica. Se partió de un circuito instalado al que se deseaba mejorar sus condiciones tanto de apariencia como de funcionalidad. Como estudio final, se evaluará la repercusión que la modificación llevada a cabo ha supuesto respecto al estado inicial.Departamento de Tecnología ElectrónicaMáster en Ingeniería Industria