Comparison and Improvement of Local Planners on ROS for Narrow Passages

Yuan, Huajun; Li, Hanlin; Zhang, Yuhan; Du, Shiyu; Yu, Limin; Wang, Xinheng

doi:10.1109/hdis56859.2022.9991270

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Reference Numbers Gazebo Simulators Gazebo only [13], [15], [18], [22], [28], [30], [33], [35], [36], [53], [78], [84]- [88], [90], [92]- [96], [98], [102], [104]- [107], [111], [112], [115], [116], [123], [125], [131], [137], [140], [143], [144], [147], [150], [151], [155], [156], [158], [159], [162], [166], [178], [181], [188], [192], [193], [195], [197], [199]-[202] Gazebo + RViz [1],…”

Section: Simulator Typementioning

confidence: 99%

“…The categorisation of WMRs into "Mobile Robots", "Self-driving Cars", and "Wheelchairs", as detailed in Table 5, presents several insights into the current state and direction of AI-driven perception and control research. The significance of the "Mobile Robot" category, particularly the TurtleBot series [2], [8], [9], [12], [25], [30], [81], [88], [100], [105], [143], [144], [147], [148], [150], [158], [178]- [181], indicates a strong focus on exploration and automation in unstructured environments. This trend may reflect the broader scientific interest in space exploration, disaster recovery, and autonomous navigation.…”

Section: Rq3: Which Ros-enabled Wmrs Are Employed In Ai-driven Percep...mentioning

confidence: 99%

See 1 more Smart Citation

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

Kargar,

Yordanov,

Harvey

et al. 2024

IEEE Access

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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 ROSenabled 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.

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