Robotic autonomous systems for earthmoving equipment operating in volatile conditions and teaming capacity: a survey

Author:

Nguyen Huynh A.D.,Ha Quang P.ORCID

Abstract

AbstractThere has been an increasing interest in the application of robotic autonomous systems (RASs) for construction and mining, particularly the use of RAS technologies to respond to the emergent issues for earthmoving equipment operating in volatile environments and for the need of multiplatform cooperation. Researchers and practitioners are in need of techniques and developments to deal with these challenges. To address this topic for earthmoving automation, this paper presents a comprehensive survey of significant contributions and recent advances, as reported in the literature, databases of professional societies, and technical documentation from the Original Equipment Manufacturers (OEM). In dealing with volatile environments, advances in sensing, communication and software, data analytics, as well as self-driving technologies can be made to work reliably and have drastically increased safety. It is envisaged that an automated earthmoving site within this decade will manifest the collaboration of bulldozers, graders, and excavators to undertake ground-based tasks without operators behind the cabin controls; in some cases, the machines will be without cabins. It is worth for relevant small- and medium-sized enterprises developing their products to meet the market demands in this area. The study also discusses on future directions for research and development to provide green solutions to earthmoving.

Publisher

Cambridge University Press (CUP)

Subject

Computer Science Applications,General Mathematics,Software,Control and Systems Engineering,Control and Optimization,Mechanical Engineering,Modeling and Simulation

Reference108 articles.

1. A deep-learning-based computer vision solution for construction vehicle detection;Arabi;Comput.-AIDED Civ. Inf.,2020

2. [85] Khokale, S. , How IoT is making heavy equipment safer and more efficient, 2019-03-19, accessed 22/04/2021, [Online]. Available: https://www.einfochips.com/blog/how-iot-is-making-heavy-equipment-safer-and-more-efficient/

3. Visual navigation using heterogeneous landmarks and unsupervised geometric constraints;Lu;IEEE Trans. Robot.,2015

4. [43] Bennink, C. , 5G Enables Advances in Machine Connectivity. accessed 22/03/2021, Feb. 10, 2020. [Online]. Available: https://www.forconstructionpros.com/construction-technology/article/21111112/5g-enables-advances-in-machine-connectivity

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