Deep Learning in Robotics for Strengthening Industry 4.0.: Opportunities, Challenges and Future Directions

Abstract

AbstractThe twenty-first century is undergoing a fundamental transition in the way things are created and services are provided. The digitalization of services has resulted in a compelling, major change in the sector, which is now referred to as Industry 4.0. One of the major changes embracing this industrial revolution is the development of robotics. Today, with the tasks becoming increasingly complex, robots are more trusted to perform the tasks with accuracy. They are rapidly substituting human skills in terms of speed, accuracy, and replaceability. Over the years, they have made vital contributions to some of the major industries, like 3D printing, autonomous vehicles, computer chip building, health and safety, agriculture, and so on. Robotics is a key Industry 4.0 technology that gives significant possibilities in the realm of production. However, with the introduction of Industry 4.0, it has become increasingly impossible for a corporation to remain relevant without incorporating some type of intelligent technology. Big data, which is generated by a wide range of sensors, necessitates complicated systems capable of distilling usable information and making intelligent judgments. This is where technology such as artificial intelligence and deep learning may help. The major result of combining these technologies with modern robotics is the creation of intelligent factories that are very powerful, safe, and cost-effective. The current research discussed the function of deep learning in robots for bolstering Industry 4.0. The authors discussed the various ways in which deep learning algorithms may be employed to improve the performance of robotics systems. Object identification, robotic grip, acoustic modelling, and motion control are the four key subjects covered in the article. A subsequent study discusses some of the significant problems for the same.KeywordsDeep learningRoboticsNeural networksObject graspingObject detectionMotion controlAcoustic modelling