PRE2017 3 Groep11

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Coaching Questions Group 11


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Contents

Problem statement and objectives

Problem statement

Objectives

  • Shorter delivery times
  • Find a way for robots to drop products in a safe but non-invasive way
  • When to use what type of drones (drone/car)
  • How to increase reliability
  • Package handling
  • Determine social impact
  • Stakeholders

Who are the users

  • Delivery services
  • Product sellers
  • Product buyers
  • Hospitals (emergency organ transportation)

What do the users require

  • Fast and reliable service
  • Low prices
  • Privacy of products
  • non-invasive service

Approach, milestones and deliverables

Approach

First we will study the literature to figure out to what extent our case is already researched. After that we will attempt to determine the present day problems with the technology. We will try to tackle all objectives, and in the end we will make a model to test our study.

Milestones

  • Literature study
    • Sources read
    • Sources summarized
    • Conclusions drawn (what are the pro’s and con’s , what will it cost, what should the infrastructure look like, what are the capabilities of different types of robots)
  • Establish rules the model should follow
    • What should the capabilities of drones/cars be

Deliverables

  • Write a report
    • User analysis
    • Financial evaluation
  • Create a model (eclipse)

Who's doing what

All together:

  • Write introduction

Everyone for themselves:

  • Search for sources (10-2)
  • Summarize sources (19-2)

Sources and summaries

Auto-Selection Of Package Delivery Location Based On Estimated Time Of Delivery

Toksoz, Tuna; Gulkaya, Tutku; and Price, Thomas, "Auto-Selection Of Package Delivery Location Based On Estimated Time Of Delivery", Technical Disclosure Commons, (December 22, 2016) http://www.tdcommons.org/dpubs_series/359

Summary

hier moet dus nog de summary van dit


Parcel delivery in an urban environment using unmanned aerial systems: a vision paper

Anbaroğlu, B., " Parcel delivery in an urban environment using unmanned aerial systems: a vision paper", ISPRS, (November, 2017) https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-4-W4/73/2017/isprs-annals-IV-4-W4-73-2017.pdf

Summary

The development of UAV’s started in the military. From there on, the technology spread to many other sectors that also benefit from it for performing various tasks. For this article, the use of drones for delivery purposes is considered. For now, the public still has a rather negative image of drones, as most people fear privacy violations. Professional UAV pilots, however, more fear the risk of possible accidents. The use of drones to deliver goods also has a lot of benefits. Firstly, they replace trucks, which saves a lot of space on the road and pollution. Thereby, drone delivery is good for the economy and employment, because of all development and manufacturing needed to make drone delivery systems. In short, it is cheaper, faster, safer and better for the environment. In order to get to a real implementation of drone delivery, there are three important challenges to overcome: public acceptance, regulations and technology. For public acceptance, the biggest challenges are privacy, safety and reliability. Considering regulations, the biggest problems are the tracking of the UAV’s, the identification of non-authorised UAV’s, hacking prevention and routing of the UAV’s, in order to prevent accidents. The technological challenges are mostly related to the battery life, avoiding other things and big buildings blocking GPS signals.

The Sky’s (Not) the Limit - Influence of Expertise and Privacy Disposition on the Use of Multicopters

Lidynia, Chantal; Philipsen, Ralf; Ziefle, Martina, " The Sky’s (Not) the Limit - Influence of Expertise and Privacy Disposition on the Use of Multicopters ", Springer, (June 21, 2017) https://link.springer.com/chapter/10.1007/978-3-319-60384-1_26

Summary

The development of UAV’s started in the military. From there on, the technology spread to many other sectors that also benefit from it for performing various tasks. For this article, the attitude of certain groups of people towards drones is considered. In general, the attitude towards drones is rather positive. There are some concerns, however. The general public is mostly concerned about privacy, whereas professional drone pilots are mostly concerned about possible accidents. It is also mentioned that ‘privacy’ is a rather vague, ill-defined, thing, that also changes as a result of new technologies and other developments. Looking at the current legal situation, it becomes clear that none of the current legal restrictions for private drone usage is perceived as overly restrictive. Some general concerns towards drones(apart from the ones already mentioned) are the ue of drones as a weapon, misuse by criminals and spying. One last thing that is discussed by the article is the fact that people only really agree by drones flying over their houses is in case of rescue operations. For some other things, such as drone delivery, people only slightly approve this.


Post-Production Analysis Approach for drone delivery fleet

Asma, Troudi; Addouche, Sid-Ali; Dellagiy, Sofiene; El Mhamedi, Abderrahman; "Post-Production Analysis Approach for drone delivery fleet", IEEE Explore digital library, (December 01, 2017) http://ieeexplore.ieee.org/document/8120986/

Summary

Nowadays, a lot of companies are investing in drone delivery services, such as DHL with PaketKopter, Amazon with Amazon PrimeAir , Google with Project Wing and recently GeoPoste with Geodrone. In order to get drone delivery working good, there needs to be a very good management and Logistics Support in order to be reliable, cheap and fast enough. The subject of this article is the Logistics Support part of this. Logistics support should consists of two parts according to this article:

  • Prerequisite SL recommended by the manufacturer through an operating manual. (This is not enough, so this paper proposes the following:)
  • Post-Production logistics support system which depends on the exploitation requirements

The article also states that ‘’the identification of the fleet status, the health status or also maintenance facilities, helps to support the system during the exploitation phase’’. Also, maintenance is important in order to get an as high as possible availability. Logistics Support Analysis is used to increase efficiency of maintenance and reduces the cost of providing support by preplanning all aspects of Logistics Support. In this analysis, the article also suggests a new part, in order to also be able to take future changes into account (For example, when a drone fleet is equipped with a new battery, there will be a lot of implications for the entire infrastructure). This new part is called an Activity Analysis. In this Activity Analysis, all implications of a possible future change are evaluated and prepared for. Lastly, a model is made to optimize the total travelling distance of the UAV’s.

A multi-objective green UAV routing problem

Coelho, Bruno N.; Coelho, Vitor N.; Coelho, Igor M.; Ochi, Luiz S.  ; Haghnazar K., Roozbeh; Zuidema, Demetrius;. Lima, Milton S.F; da Costa, Adilson R., "A multi-objective green UAV routing problem", Elsevier, (December, 2017) https://www.sciencedirect.com/science/article/pii/S0305054817301028?via%3Dihub

Summary

The development of UAV’s started in the military. From there on, the technology spread to many other sectors that also benefit from it for performing various tasks. Nowadays, the biggest problems for the development of delivery drones are the very strict rules for drones (no flying in urban environments, drone must stay in sight of pilot, etc.) and the limited battery life of a drone. This paper considers a Green UAV Routing Problem (GUAVRP), which minimizes seven objective functions: total traveled distance; UAV’s maximum speed; number of used vehicles; makespans of the last collected and delivered package; average time spent with each package; and maximize batteries load at the end of the schedule. For the model, it is assumed that there are two flight levels: one low level for smaller drones and a higher level for bigger ones. In the map, there are also several refueling stations. According to the article ‘’The main contributions of this current work are:

  • Develop a mathematical programming model for a time- dependent UAV heterogeneous fleet routing problem, in particular:
    • respecting UAVs operational requirements;
    • tackling the micro-airspace considering a multi-layer scenario with package exchanging points;
    • integrating UAVs into the new concepts of mini/microgrid systems, in which vehicles can be charged at different points of the future smart cities.
  • Consider a multi-objective optimization framework in order to provide alternative solutions with different possible routes and schedules.’’

There are no real conclusions in this paper, it is mostly about making the model itself.

The Vehicle Routing Problem with Drones: Extended Models and Connections

Poikonen, Stefan; Wang, Xingyin; Golden, Bruce, “The Vehicle Routing Problem with Drones: Extended Models and Connections”, Wiley online library, (June 7, 2017) http://onlinelibrary.wiley.com/doi/10.1002/net.21746/full

summary

This article considers a truck that is carrying drones, so it is a combination of both drone and truck delivery. In short, they looked at the difference between a lot of slow drones and some fast drones. They found that if there are times when not all drones are in service (service not fully parallelized), greater drone speed dominates and if drone range or capacity is severely limited, a larger number of drones may dominate. Also, they stated that a drone will, for any destination, always travel a shorter (or just as long) path than a truck, because a drone isn’t bound to roads. Then, they also considered some routing problems, namely Close-enough-vehicle-routing-problem(CEVRP), vehicle-routing-problem-with-drones(VRPD) and vehicle-routing-problem(VRP) (CEVRP and VRP being known problems, and VRPD being the problem of this article). They found that CEVRP gives the optimal solutions of VRPD when the velocity of the drones is infinite and that VRP gives the optimal solution of the VRPD when the velocity of the drones is 0.

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