The Raven Open Surgical Robotic Platforms: A Review and Prospect

doi:10.12700/aph.16.8.2019.8.2

Cited by 3 publications

(3 citation statements)

References 59 publications

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“…• Safety and reliability: ensuring the safety and reliability of robots, especially in critical applications, is a major challenge. This requires the development of robust fault-tolerance and safety mechanisms, as well as rigorous testing and validation of the robot's performance (Li et al, 2013(Li et al, , 2017cAlemzadeh et al, 2016;Li, 2019;Li Y. et al, 2019). • Scalability: developing robots that can operate effectively in different environments and perform a wide range of tasks is a difficult challenge.…”

Section: Deep Causal Learning For Robotic Intelligence Challenges I...mentioning

confidence: 99%

Deep causal learning for robotic intelligence

2023

Front. Neurorobot.

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This invited Review discusses causal learning in the context of robotic intelligence. The Review introduces the psychological findings on causal learning in human cognition, as well as the traditional statistical solutions for causal discovery and causal inference. Additionally, we examine recent deep causal learning algorithms, with a focus on their architectures and the benefits of using deep nets, and discuss the gap between deep causal learning and the needs of robotic intelligence.

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Section: Deep Causal Learning For Robotic Intelligence Challenges I...mentioning

confidence: 99%

Deep causal learning for robotic intelligence

2023

Front. Neurorobot.

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“…The humanoid platforms studied and used most often in student projects are iCub (RobotCub Consortium) and NAO (Aldebaran Robotics). These robots have also been used in many scientific papers to help children or people with disabilities [22][23][24] [25].…”

Section: Cognitive Robotics Platformsmentioning

confidence: 99%

Cognitive robotics software development aspects based on experiments of future software engineers

Demeter

Kővári

Katona

et al. 2020

2020 11th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)

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Machine learning algorithms are widely used in the domain of robotics. In particular, applications using machine learning and artificial intelligence algorithms have led to promising results in industrial applications, cognitive robotics and thus gained attention in recent years. In this context, the purpose of this article is to present the technologies and architectures used in the design and development of cognitive robots by students. This study highlights the difficulties encountered by future engineers in developing research projects in robotics.

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“…In 2006, the 9th NEEMO project led a team to build a mobile M7 surgical robot to perform abdominal surgery on a patient simulator with a 3-second earthmoon communication delay via microwave and satellite links. In 2007, as part of the 12th NEEMO project, the feasibility of telesurgery using the Raven robot and his M7 robot was measured [13,14]. Staff performed zero-gravity stitches under the guidance of Seattle, Washington.…”

Section: -Introductionmentioning

confidence: 99%

SY-MIS Project: Biomedical Design of Endo-Robotic and Laparoscopic Training System for Surgery on the Earth and Space

Cornejo,

Vargas

et al. 2024

Emerg Sci J

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Despite the location (Earth or Space), surgical simulation is a vital part of improving technical skills and ensuring patients' safety in the real procedure. The purpose of this study is to describe the Space System for Minimally Invasive Surgery (SY-MIS©) project, which started in 2016 under the supervision of the Center for Space Systems (C-SET). The process connects the best features of the following machines: Biomedik Surgeon, Space Biosurgeon, SP-LAP 1, and SP-LAP 2, which were defined using the VDI 2221 guidelines. This research uses methods based on 3 standards: i) Biomedical design: ISO 9001-13485 / FDA 21 CFR 820.30 / ASTM F1744-96(2016); ii) Aerospace human factors: HF-STD-001; iii) Mechatronics design: VDI 2206. The results depict the conceptual biomedical design of a novel training system named Surgical Engineering and Mechatronic System (SETY©), which integrates the use of 2 laparoscopic tools and 2 anthropomorphic mini-robotic arms (6 DOF). It has been validated by the Evaluation of Technical Criteria, getting a total score of 90% related to clinical assessment, machine adaptability, and robustness. The novelty of the research lies in the introduction of a new procedure that covers the simultaneous use of laparoscopic and robotic systems, named Hybrid Cyber-Physical Surgery (HYS©). In conclusion, the development of SY-MIS© promotes the use of advanced technologies to improve surgical procedures and human-machine medical cooperation for the next frontier of habitability on other planets. Doi: 10.28991/ESJ-2024-08-02-01 Full Text: PDF

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The Raven Open Surgical Robotic Platforms: A Review and Prospect

Cited by 3 publications

References 59 publications

Deep causal learning for robotic intelligence

Deep causal learning for robotic intelligence

Cognitive robotics software development aspects based on experiments of future software engineers

SY-MIS Project: Biomedical Design of Endo-Robotic and Laparoscopic Training System for Surgery on the Earth and Space

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