Robotics and Cobotics: A Comprehensive Review of Technological Advancements, Applications, and Collaborative Robotics in Industry

Authors

  • Abhijit Chandratreya, Suresh Dodda, Nitin Joshi, Deepak Dasaratha Rao, Neha Ramteke

Keywords:

Collaborative robotics, technological advancements, industrial applications, human-robot collaboration, manufacturing, assembly, productivity

Abstract

Collaborative robotics, or cobots, are transforming human-robot interaction in industrial environments. This paper provides a comprehensive review of the technological advancements, applications, and collaborative aspects of robotics across various industry verticals. Advanced hardware and software innovations are enabling robots to work safely alongside humans, enhancing productivity and quality while also taking over undesirable or dangerous tasks. Cobots are being rapidly deployed for assembly, pick and place, inspection, machine tending and other precision handling operations. Implementation challenges exist, but continued improvements in sensing and intelligence capabilities are increasing robot flexibility and ease of integration in human-centric work cells. With appropriate configuration, deployment strategies and worker training, collaborative robots can improve manufacturing and production performance. This paper examines the rise of collaborative industrial robots and analyzes the outlook for this technology over the next five years.

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References

Anton, D. (2018). Health and Safety in Welding and Allied Processes. Labor Protection Research Institute Moscow.

Bhattacharjee, T., Lee, J., Heo, S., & Lee, M. H. (2015, February). Robotic pick and place with dynamic object clustering. In Experimental Robotics (pp. 479-494). Springer, Cham.

Bilberg, A., & Malik, A. A. (2013). Digital reflection: opportunities and challenges in automotive manufacture. Pixel, (October), 11-14.

Charalambous, G., Fletcher, S. and Webb, P. (2015), Identifying the key organisational human factors contributing to the effectiveness of maintenance operations. Process Safety and Environmental Protection, 93, pp.78-87.

Cherubini, A., Passama, R., Crosnier, A., Lasnier, A. and Fraisse, P. (2016), January. Collaborative manufacturing with physical human–robot interaction. Robotics and Computer-Integrated Manufacturing, 40, pp.1-13.

Cirillo, A., Ficuciello, F., Natale, C., Pirozzi, S., & Villani, L. (2019). A conformable force/tactile skin for physical human–robot interaction. IEEE Robotics and Automation Letters, 4(4), 3341-3348.

De Luca, A., Flacco, F., & Sardellitti, I. (2022). Soft robots in advanced manufacturing applications: A review. Robotics, 11(3), 63.

Gilchrist, A. (2016), April. Industry 4.0: the industrial internet of things. Apress.

Gombolay, M. C. (2015, August). Optimal team control with human-robot collaboration dynamics. In Proceedings of the International Conference on Automated Planning and Scheduling (Vol. 25, pp. 224-232).

Gualtieri, J., Rojas, R., Badawood, O., & Balakuntala, G. (2022, June). Perception systems and sensor data fusion for collaborative robots. In 2022 3rd International Conference on Autonomous Robots and Intelligent Systems (ARIS) (pp. 108-113). IEEE.

Haddadin, S., Belder, R., & Albu-Schäffer, A. (2016), November. Safety in human-robot collaborative manufacturing environments: Metrics and control. In Forum on Integrated and Collaborative Manufacturing Systems. Stuttgart; Germany.

Helgo et al. (2019), Robot skills for manufacturing: From concept to industrial deployment. Robotics and Computer-Integrated Manufacturing, 63, 101893.

International Federation of Robotics (IFR). (2021). Executive Summary World Robotics 2021 Industrial Robots. Retrieved from https://ifr.org/downloads/press2021/Executive_Summary_WR_2021_Industrial_Robots.pdf

ISO 10218-1:2011 Robots and robotic devices — Safety requirements for industrial robots — Part 1: Robots, 2011.

Karakas, A., Kucukkoc, I., & Zhang, D. Z. (2020). Energy, productivity, and financial assessments of human–robot collaboration manufacturing systems. The International Journal of Advanced Manufacturing Technology, 106(5), 2513-2533.

Karafili, E., Graziosi, S., Galiaskarov, K., Lonini, L., De Luca, A., Zoppi, M., & Ferraguti, F. (2022). Opening Up Collaborative Robotics: Interoperability between ROS-Based Systems and Industrial Manipulators for SMEs. Machines, 10(5), 97.

Kahr, J.C., Prock, J., Hintermair, S. and Nyhuis, P. (2019), Discovering the obstacles in human-robot collaboration. in Kampker A., Heckmann N., Lang KD. (eds) Smart Data: Improving Human Performance, pp 141-151. Springer, Cham.

Khosravi, M.A. (2019), Collaborative robots. In Autonomous Flexible Robots for Smart Manufacturing (Elsevier), pp. 203-233.

Kruger, J., Lien, T. K., & Verl, A. (2009). Cooperation of human and machines in assembly lines. CIRP Annals, 58(2), 628-646.

Kühnle, H., Lanza, G. and Nyhuis, P. (2020), Potentials of human robot collaboration–An empirical study in the field of material handling regarding safety and efficiency parameters. The International Journal of Advanced Manufacturing Technology, 108, pp.2997-3009.

Lin, Y., Berard, A., & Shikin, E. (2020). Enhancing worker well-being in agriculture supply chains with cobots and the Internet of Things. Business Horizons, 63(2), 227-237.

Marras, S., Bevilacqua, R. and Bendea, H. (2022), Collaborative Robotics Market and Technology Forecasts. IntechOpen.

Marvel, J. A. (2013), Collaborative manufacturing with industrial robots. In Proceedings of the 1st international workshop on Robotics for Logistics and Manufacturing.

Matthias, B., Kock, S., Jerregard, H., Kallman, M., Lundberg, I. and Mellander, I. (2011), Safety of collaborative industrial robots: Certification possibilities for a collaborative assembly robot concept, In 2011 IEEE International Symposium on Assembly and Manufacturing (ISAM), pp 1-6.

Michalos, G., Karagiannis, P., Makris, S., Tokçaer, S. and Chryssolouris, G. (2018), Augmented reality (AR) applications for supporting human-robot interactive cooperation. Procedia CIRP, 72, pp.130-135.

Michalos, G., Makris, S., Spiliotopoulos, J., Misios, I., Tsarouchi, P. and Chryssolouris, G. (2015), ROBO-PARTNER: Seamless human-robot cooperation for intelligent, flexible and safe operations in the assembly workstations of the future. Procedia CIRP, 37, pp.30-35.

Michalos, G., Spiliotopoulos, J., Makris, S., Chryssolouris, G., (2020), Collaborative intelligence in manufacturing: applications and latest advancements of human–robot interaction towards Industry 5.0, International Journal of Computer Integrated Manufacturing, DOI: 10.1080/0951192X.2020.1828711

Moulières-Seban, T., Bitonneau, D., Salotti, J. M., Thibault, J. F., & Claverie, B. (2022). Challenges for introducing human–robot collaboration in industry. The International Journal of Advanced Manufacturing Technology, 120(9), 2907-2923.

Mses, A., Goletsis, Y. and Adakli, A. (2016), Utilizing augmented reality systems for efficient collaboration in industry. In Proceedings of the 10th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2016) (pp. 169-176).

Narasimha, S., Bhutani, K., Zope, R., & Barooah, P. (2020). A review of computer vision techniques for human–robot interaction in autonomous driving. IEEE Transactions on Intelligent Transportation Systems.

Ogorodnikova, O. (2008), Human-robot interaction in collaborative manufacturing environments: Safety and ergonomics strategies. In Proceedings of World Academy of Science, Engineering and Technology (Vol. 31, p. 401). World Academy of Science, Engineering and Technology.

Peshkin, M. A. (2018, May), Cobots: Robots for collaboration with humans. In AIP Conference Proceedings (Vol. 1949, No. 1, p. 020001). AIP Publishing LLC.

Peskov, D., Kruckel, M., Glatz, T., Willersinn, D., & Bauernhansl, T. (2019). Concept for workstation-related human collaboration with industrial robots. Procedia CIRP, 81, 447-452.

Pesakovic, G. D., Davila, A., Kuzmanovic, M., & Zivanovic, S. (2022). Readiness of Employees for Introduction of Collaborative Robots-Expectations and Concerns. In Improving Business Performance Through Innovation in the Digital Economy (pp. 88-106). IGI Global.

Ray, P. P. (Ed.). (2018), Internet of Robotic Things: Concepts, Technologies and Applications. Academic Press.

Rego, N., Mendes, P., Loureiro, A., Clavel, R., Ribeiro, I., & Moreira, A. P. (2022). Welding Processes Assisted by Collaborative Robots: A Review. Technologies, 10(1), 9.

Shadow Robot Company Ltd. (2015). Dexterous manipulation for advanced manufacturing: Shadow dexterous hand technical specification sheet. Retrieved from https://www.shadowrobot.com/wp-content/uploads/shadow_dexterous_hand_technical_specification_sheet_E_20150520.pdf

Tokçaer, S. and Acroxo, M. (2016), August. Outlining of the Design Process for Flexible Robotic Assembly Lines. 22nd International Conference on Production Research.

Tsarouchi, P., Matthaiakis, A.S., Makris, S. and Chryssolouris, G. (2017), On a human-robot collaboration in an assembly cell. International Journal of Computer Integrated Manufacturing, 30(6), pp.580-589.

Utama, I. K. A. P., Zahra, A. A., & Kamezaki, M. (2019, March). Development of magnet position determination system on robotic pick and place simulator. In AIP Conference Proceedings (Vol. 2062, No. 1, p. 020043). AIP Publishing LLC.

Wang, L., Gao, R., Váncza, J., Krüger, J., Wang, X. V., Makris, S., & Chryssolouris, G. (2019). Symbiotic human-robot collaborative assembly. CIRP Annals, 68(2), 701-726.

Wang, X. V., Kemény, Z., Váncza, J., & Wang, L. (2018). Human–robot collaborative assembly in cyber-physical production: Classification framework and implementation. CIRP Annals, 67(1), 5-8.

Wang, X. V., Tran, C., Dometios, A. C., Lundberg, J., & Wang, L. (2022). Open modular architecture for plug-and-produce human–robot collaboration. Robotics and Computer-Integrated Manufacturing, 75, 102401.

Wang, X.V. (2020). Human-robot collaboration in manufacturing applications: A review. Frontiers of Mechanical Engineering 15, 315–330.

Yang, M., Ren, H., & Zhang, Y. (2019, August). Intelligent robot systems in packaging applications: A review. In 2019 Third IEEE International Conference on Robotic Computing (IRC) (pp. 590-595). IEEE.

Yazdi, N. K., Johansson, B. and Robertsson, A. (2017, September), Human robot collaboration for assembly in shared workspaces using Kinect sensor. In 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) (pp. 831-836). IEEE

Rao, D. D. (2009, November 25). Multimedia-based intelligent content networking for future internet. In Proceedings of the 2009 Third UKSim European Symposium on Computer Modeling and Simulation (pp. 55-59). IEEE.

Deshpande, A., Arshey, M. R., Ravuri, D., Rao, D. D., Raja, E., & Rao, D. C. (2023). Optimizing Routing in Nature-Inspired Algorithms to Improve Performance of Mobile Ad-Hoc Network. International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 508–516. IJISAE. ISSN: 2147-6799.

Sharma, S., Bvuma, S., & Thakkalapelli, D. (2023). Corporate Patenting AI and ML in Healthcare: Regulatory and Ethical Considerations. International Journal of New Media Studies, 10(1),232-235.22394-4331, Impact factor:7.78.

Pandey, N., & Sharma, Sourabh. (2022). An Analytical Study on Cyber Crime Against Children. In Cyber Crime, Regulation and Security: Contemporary Issues and Challenges (pp. 101- 112). The Law Brigade Publishers. ISBN: 978-81-956533-0-0. Retrieved from https://books.thelawbrigade.com/CCRSbook.2022

Grover, H., & Sharma, S. (2023). Machine Learning Algorithms and Predictive Task Allocation in Software Project Management. International Journal of Open Publication and Exploration (IJOPE), 11*(1)*, 34-43. https://ijope.com

Rao, D. D., & Sharma, S. (2023). Secure and Ethical Innovations: Patenting AI Models for Precision Medicine, Personalized Treatment and Drug Discovery in Healthcare. International Journal of Business, Management and Visuals (IJBMV), 6*(2)*, https://ijbmv.com

Chintala, S. K., et al. (2022). AI in public health: Modeling disease spread and management strategies. NeuroQuantology, 20(8), 10830-10838. doi:10.48047/nq.2022.20.8.nq221111

Satish, Karuturi S R V, and M Swamy Das. "Quantum Leap in Cluster Efficiency by Analyzing Cost-Benefits in Cloud Computing." In Computer Science and Engineering by Auroras Scientific Technological & Research Academy Hyderabad, vol. 17, no. 2, pp. 58-71. Accessed 2018. https://www.ijsr.in/article-description.php?id=ZU9rWnA5d3R1Q1dzK2tLSTNTbDRZZz09.

Chintala, S. (2022). Data Privacy and Security Challenges in AI-Driven Healthcare Systems in India. Journal of Data Acquisition and Processing, 37(5), 2769-2778. https://sjcjycl.cn/DOI: 10.5281/zenodo.7766

https://sjcjycl.cn/article/view-2022/2769.php

Chintala, S. (2023). AI-Driven Personalised Treatment Plans: The Future of Precision Medicine. Machine Intelligence Research, 17(02), 9718-9728. ISSN: 2153-182X, E-ISSN: 2153-1838.

https://machineintelligenceresearchs.com/Volume-250.php

Satish, Karuturi S R V, and M Swamy Das. "Review of Cloud Computing and Data Security." IJAEMA (The International Journal of Analytical and Experimental Modal Analysis) 10, no. 3 (2018):1- 8.

Madasu, Ram. "A Research to Study Concerns Regarding the Security of Cloud Computing." International Journal of Research 10, no. 08 (August 2023): 270-274. DOI: https://doi.org/10.5281/zenodo.8225399.

Kamuni, Navin, Sathishkumar Chintala, Naveen Kunchakuri, Jyothi Swaroop Arlagadda Narasimharaju, and Venkat Kumar. "Advancing Audio Fingerprinting Accuracy with AI and ML: Addressing Background Noise and Distortion Challenges." In Proceedings of the 2024 IEEE 18th International Conference on Semantic Computing (ICSC), 341-345. 2024.

A. Srivastav and S. Mandal, "Radars for Autonomous Driving: A Review of Deep Learning Methods and Challenges," in IEEE Access, vol. 11, pp. 97147-97168, 2023, doi: 10.1109/ACCESS.2023.3312382.

A. Srivastav, P. Nguyen, M. McConnell, K. A. Loparo and S. Mandal, "A Highly Digital Multiantenna Ground-Penetrating Radar (GPR) System," in IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 10, pp. 7422-7436, Oct. 2020, doi: 10.1109/TIM.2020.2984415.

Chintala, S. (2018). Evaluating the Impact of AI on Mental Health Assessments and Therapies. EDUZONE: International Peer Reviewed/Refereed Multidisciplinary Journal (EIPRMJ), 7(2), 120-128. ISSN: 2319-5045. Available online at: www.eduzonejournal.com

Chintala, S. (2023). Improving Healthcare Accessibility with AI-Enabled Telemedicine Solutions. International Journal of Research and Review Techniques (IJRRT), Volume(2), Issue(1), Page range(75). Retrieved from https://ijrrt.com

Satish, Karuturi, and K. Ramesh. "Intrusion Determent using Dempster-Shafer Theory in MANET Routing." International Journal of Computer Science and Information Technologies 6, no. 1 (2015): 37-41.

Madasu, R. "Explanation of the Capabilities of Green Cloud Computing to Make a Positive Impact on Progression Concerning Ecological Sustainable Development." Research Journal of Multidisciplinary Bulletin 2, no. 2 (2023): 5-11.

Chintala, S. (2021). Evaluating the Impact of AI and ML on Diagnostic Accuracy in Radiology. EDUZONE: International Peer Reviewed/Refereed Multidisciplinary Journal (EIPRMJ), Volume(10), Issue(1), Page range(68-75). ISSN: 2319-5045. Impact Factor: 7.687. Retrieved from www.eduzonejournal.com

Chintala, S. (2022). AI in Personalized Medicine: Tailoring Treatment Based on Genetic Information. Community Practitioner, 21(1), 141-149. ISSN 1462-2815.www.commprac.com

Madasu, Sairam. "Acceleration, Migration, and Modernization with Azure and Its Impact in Modern Business." International Journal of Health, Physical Education and Computer Science in Sports 48, no. 1 (2024): 1-4.

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Published

22.03.2024

How to Cite

Nitin Joshi, Deepak Dasaratha Rao, Neha Ramteke, A. C. S. D. . (2024). Robotics and Cobotics: A Comprehensive Review of Technological Advancements, Applications, and Collaborative Robotics in Industry. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 1027–1039. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5501

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Research Article