Automated Loading and Unloading Operations: A Systematic Review

Paper i proceeding, 2023

Purpose

Material handling has witnessed changes with automations occurring in the transport sector.

The increasing implementation of autonomous trucks lays questions on the loading and

unloading operations that the conventional truck driver used to perform. Loading and unloading

operations interface warehouses and transportation. Conventionally characterised by the

manual operating nature causing inefficiencies and discontinuities, automated loading and

unloading (ALUL) benefit by enhancing workflows, improves performance, and reduces

losses. Despite these benefits, research on ALUL is minimal. This article i) details focus of

ALUL systems in research, ii) indicates adopted evaluation indicators and iii) highlights key

enablers and impediments witnessed during implementation.

Methodology

Developments are assessed by carrying out a systematic literature review including published

literature, technical articles etc. Review is initiated by identifying appropriate keywords,

coupled with Boolean operators, to retrieve literature from scientific databases.

Findings

Research on LUL reveal a classified research focus on perception systems, manipulators, and

general solution type. Operating time was identified to be a commonly evaluated performance

parameter despite research revealing diverse parameters. The review highlights i) variable

loading and unloading methods with changing good types. ii) Complexities in identifying and

manipulating goods. iii) Frequent human involvement, and iv) high implementation costs and

associated infrastructural modifications to influence implementation despite many enablers

supporting the implementation of this technology. Despite the above issues, commercial

solutions with varied degrees of automation are available and are listed in this article.

Practical implications

ALUL systems are described comprehensively providing a detailed representation of existing

knowledge regarding ALUL, making selection easier for interested industries and guiding them

through the transformation process.

Originality

Research aids in determining function-specific systems enabling a detailed understanding of

ALUL systems.