Autonomous Heavy-Duty Mobile Machinery: A Multidisciplinary Collaborative Challenge

Abstract

Heavy-duty mobile machines (HDMMs) are a wide range of machinery used in diverse and critical application areas which are currently facing several issues like skilled labor shortage, poor safety records, and harsh work environments. Consequently, efforts are underway to increase automation in HDMMs for increased productivity and safety, eventually transitioning to operator-less autonomous HDMMs to address skilled labor shortages. However, HDMM are complex machines requiring continuous physical and cognitive inputs from human-operators. Thus, developing autonomous HDMM is a huge challenge, with current research and developments being performed in several independent research domains. Through this study, we use the bounded rationality concept to propose multidisciplinary collaborations for new autonomous HDMMs and apply the transaction cost economics framework to suggest future implications in the HDMM industry. Furthermore, we introduce a conceptual understanding of collaborations in the autonomous HDMM as a unified approach, while highlighting the practical implications and challenges of the complex nature of such multidisciplinary collaborations. The collaborative challenges and potentials are mapped out between the following topics: mechanical systems, AI methods, software systems, sensors, connectivity, simulations and process optimization, business cases, organization theories, and finally, regulatory frameworks.

A design space for automated material handling vehicles

“…There is a high business interest and considerable growth prospects with regard to achieving higher autonomy levels (Krug et al, 2019;Gupta et al, 2022). The strive for automatizing material handling vehicles is also motivated by ongoing driver shortage (Costello and Suarez, 2015), the need to increase the attractiveness of work within harsh environments, as well as to reduce safety risks (Machado et al, 2021b). However, despite the longstanding experience and growing relevance of such systems for automated handling of heavy materials, there is surprisingly little open scientific literature available about contextual factors and HMI design, and if available, it is scattered across different sub-disciplines (Krug et al, 2019;Machado et al, 2021b).…”

“…The strive for automatizing material handling vehicles is also motivated by ongoing driver shortage (Costello and Suarez, 2015), the need to increase the attractiveness of work within harsh environments, as well as to reduce safety risks (Machado et al, 2021b). However, despite the longstanding experience and growing relevance of such systems for automated handling of heavy materials, there is surprisingly little open scientific literature available about contextual factors and HMI design, and if available, it is scattered across different sub-disciplines (Krug et al, 2019;Machado et al, 2021b). For such situations with little knowledge about the context variables, general scope, and design alternatives, a design space can help to provide a generic means of orientation.…”

“…Along with the continuous automation of public and private transport as well as manufacturing environments, material handling is another context that sees increasing automation efforts (Machado et al, 2021a;Machado et al, 2021b;Li et al, 2018;Efthymiou and Ponis, 2019). Not only does the number of employed front loaders, excavators, bulldozers, forwarders, mobile cranes, and other material handling vehicles increase, but their degrees of automation do as well (Ha et al, 2018;Heath, 2018;Frank, 2019), thus increasing in-context complexity on two levels.…”

Automatic Estimation of Excavator’s Actual Productivity in Trenching and Grading Operations Using Building Information Modeling (BIM)

“…Also, these machines are powered by diesel engines, which emit a great amount of CO 2 when burning fossil fuels. In addition, it has been discovered that the cost of the equipment utilized in a construction project may account for 5% to 10% of the direct costs and up to 40% of the direct costs in a highway construction project [1,2].…”

An Approach for Estimation of Swing Angle and Digging Depth During Excavation Operation

“…In order to reduce costs, the effects of the challenges, and also to increase the productivity of mobile machines, autonomous HD-MMs are one main solution. Proposing one autonomous method for all HDMMs is highly complicated since there are a lot of mobile machines in different sizes, shapes, and functions [3].…”