Emerging Trends in Realistic Robotic Simulations: A Comprehensive Systematic Literature Review

Kargar, Seyed Mohamad and Yordanov, Borislav and Harvey, Carlo and Asadipour, Ali (2024) Emerging Trends in Realistic Robotic Simulations: A Comprehensive Systematic Literature Review. IEEE Access. ISSN 2169-3536

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Abstract

Simulation plays a pivotal role in providing safely reproducible scenarios to evaluate the ever-advancing domain of computer science and robotics. It was an essential part of the pandemic when no access to physical spaces was available. The advent of AI-powered platforms in conjunction with enhanced graphics, physics and other sensory engines attracts a new breed of interdisciplinary researchers to enter the robotic field, most notably from computer science, engineering and social sciences. Integration of ROS as a uniform middleware to deploy achieved outcomes in real practice provides an opportunity to move one step closer to the sim-to-real experiences that enables researchers to test ideas beyond the close laboratory spaces. There is a lack of comprehensive evaluation of ROS-enabled simulators, and the integration of advanced AI techniques for realistic scenario replication. This paper addresses this challenge by evaluating ROS-enabled simulators in the design and implementation of AI techniques through an in-depth systematic literature review (SLR). This SLR is guided by the research and commercial market demands, employing Population, Intervention, Comparison, Outcome, and Context (PICOC) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) frameworks with a major focus on Wheeled Mobile Robots (WMRs). We also highlight the increasing importance of game engines like Unity and Unreal in future of robotic simulations, especially under modelling close to real experiences. By comparing simulation platform features and capabilities, this paper offers guidance to developers and researchers, enabling them to select the most suitable platform for their projects efficiently that contradicts the commonly in use “one size fits all” approach. Finally, based on the thorough insights from the review, we identify and suggest some key future research directions in AI-enhanced realistic robotic simulations.

Item Type: Article
Identification Number: https://doi.org/10.1109/ACCESS.2024.3404881
Dates:
DateEvent
20 May 2024Accepted
23 May 2024Published Online
Uncontrolled Keywords: Simulation, Artificial Intelligence, Robot Operating System, Wheeled Mobile Robot
Subjects: CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-01 - engineering (non-specific)
CAH11 - computing > CAH11-01 - computing > CAH11-01-05 - artificial intelligence
CAH11 - computing > CAH11-01 - computing > CAH11-01-08 - others in computing
Divisions: Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User: Borislav Yordanov
Date Deposited: 25 Jun 2024 10:42
Last Modified: 25 Jun 2024 10:42
URI: https://www.open-access.bcu.ac.uk/id/eprint/15576

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