The adoption of self-driving delivery robots in last mile logistics

Chen, Cheng; Demir, Emrah; Huang, Yu‐An; Qiu, Rongzu

doi:10.1016/j.tre.2020.102214

Cited by 105 publications

(74 citation statements)

References 25 publications

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“…Notably, a small stream of research has started to investigate shoppers' adoption of contactless deliveries in response to the pandemic, such as delivery robots [45,46] and delivery apps [47,48]. Some researchers have even raised the following question: Is the COVID-19 pandemic strong enough to change online order delivery methods?…”

Section: Research Context: Self-collection Servicementioning

confidence: 99%

Does COVID-19 Promote Self-Service Usage among Modern Shoppers? An Exploration of Pandemic-Driven Behavioural Changes in Self-Collection Users

Wang

Wong

Yuen

2021

IJERPH

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Due to health concerns related to COVID-19, shoppers have learned to minimise social contact by adopting various contactless self-service technologies to fulfil their consumption needs. This study explores shoppers’ behavioural changes in relation to self-service, using the special research context of e-commerce self-collection services. By synthesising insights from the health psychology literature, this study proposes an affective-cognitive-social perspective to explain the pandemic-driven behavioural changes of self-collection users. The survey instrument is used for online data collection (n = 500), and a combined (descriptive and quantitative) method is adopted for data analysis. Our results suggest that, although with a relatively weak predictive power, the affective and cognitive appraisals of health risks lead to the reinforced usage of self-collection service. This also applies to the factors of action/coping planning and subjective norm. This study theoretically contributes to the self-service literature and creates managerial implications for retailers and logistics operators.

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Section: Research Context: Self-collection Servicementioning

confidence: 99%

Does COVID-19 Promote Self-Service Usage among Modern Shoppers? An Exploration of Pandemic-Driven Behavioural Changes in Self-Collection Users

Wang

Wong

Yuen

2021

IJERPH

View full text Add to dashboard Cite

show abstract

“…The robot moves at a steady and slow pace and can safely navigate across obstacles and moving objects and thus poses no threats to bystanders. The transportation status can be monitored remotely through an app [ 40 ].…”

Section: Classification and Operation Of Medical Robotsmentioning

confidence: 99%

Applications of Healthcare Robots in Combating the COVID-19 Pandemic

Raje

Reddy

Jerbi

et al. 2021

Applied Bionics and Biomechanics

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Due to the increasing number of COVID-19 cases, there is a remarkable demand for robots, especially in the clinical sector. SARS-CoV-2 mainly propagates due to close human interactions and contaminated surfaces, and hence, maintaining social distancing has become a mandatory preventive measure. This generates the need to treat patients with minimal doctor-patient interaction. Introducing robots in the healthcare sector protects the frontline healthcare workers from getting exposed to the coronavirus as well as decreases the need for medical personnel as robots can partially take over some medical roles. The aim of this paper is to highlight the emerging role of robotic applications in the healthcare sector and allied areas. To this end, a systematic review was conducted regarding the various robots that have been implemented worldwide during the COVID-19 pandemic to attenuate and contain the virus. The results obtained from this study reveal that the implementation of robotics into the healthcare field has a substantial effect in controlling the spread of SARS-CoV-2, as it blocks coronavirus propagation between patients and healthcare workers, along with other advantages such as disinfection or cleaning.

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“…The successor of Robot Operating System (ROS) ROS2 based self-driving vehicle architecture can activate safe and reliable real-time behavior [ 43 ]. Bakioglu et al [ 44 ] proposed VIKOR and TOPSIS algorithms to prioritize risks in self-driving cars, while another group of researchers [ 45 ] proposed a self-driving delivery robot in last-mile logistics. Navigation routes, one-way streets, speech recognition, and no-entry status are all things that self-driving vehicles require [ 46 ].…”

Section: Related Workmentioning

confidence: 99%

Delicar: A Smart Deep Learning Based Self Driving Product Delivery Car in Perspective of Bangladesh

Chy

Masum

Sayeed

et al. 2021

Sensors

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The rapid expansion of a country’s economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion. Additional staff are also required to follow the delivery vehicle while it transports documents or records to another destination. This study proposes Delicar, a self-driving product delivery vehicle that can drive the vehicle on the road and report the current geographical location to the authority in real-time through a map. The equipped camera module captures the road image and transfers it to the computer via socket server programming. The raspberry pi sends the camera image and waits for the steering angle value. The image is fed to the pre-trained deep learning model that predicts the steering angle regarding that situation. Then the steering angle value is passed to the raspberry pi that directs the L298 motor driver which direction the wheel should follow. Based upon this direction, L298 decides either forward or left or right or backwards movement. The 3-cell 12V LiPo battery handles the power supply to the raspberry pi and L298 motor driver. A buck converter regulates a 5V 3A power supply to the raspberry pi to be working. Nvidia CNN architecture has been followed, containing nine layers including five convolution layers and three dense layers to develop the steering angle predictive model. Geoip2 (a python library) retrieves the longitude and latitude from the equipped system’s IP address to report the live geographical position to the authorities. After that, Folium is used to depict the geographical location. Moreover, the system’s infrastructure is far too low-cost and easy to install.

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The adoption of self-driving delivery robots in last mile logistics

Cited by 105 publications

References 25 publications

Does COVID-19 Promote Self-Service Usage among Modern Shoppers? An Exploration of Pandemic-Driven Behavioural Changes in Self-Collection Users

Does COVID-19 Promote Self-Service Usage among Modern Shoppers? An Exploration of Pandemic-Driven Behavioural Changes in Self-Collection Users

Applications of Healthcare Robots in Combating the COVID-19 Pandemic

Delicar: A Smart Deep Learning Based Self Driving Product Delivery Car in Perspective of Bangladesh

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