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Presently, robotics is one of the promising fields of science and engineering which is used to build, design and manufacture robot. There is wide range of applications of robot such as automobile industry, manufacturing industry, medical science and smart factory. In Industry 4.0, wireless sensor network should be the promising technology which is being proposed into the manufacturing industry. In smart factory, robotic system plays an important role to operate the factory automatically. Robotic manipulator can be operated through wire or wirelessly. In modern times, wirelessly operated manipulator is one of the rising areas in smart factory. In smart factory, if the radioactive zone exists, so human may encounter some difficulties to operate the factory due to radioactive ray which badly affects the human cells. Therefore, to operate the robotic manipulator wirelessly is one of the key concerns. Therefore, to make wireless operation, wireless sensor networks (WSNs) should be the emerging field in smart factory and incorporation of machine learning (ML) algorithms is able to enhance the WSNs performance in terms of various matrices such as cluster formation, cluster head (CH) selection, data trans-receiving or routing and fault-tolerant scheme by which the life of the sensor network is being enhanced. ML techniques and their learning procedure are also used for localization, incident detection, object tracking in the introduced autonomous system. This chapter primarily centres on the integration of wireless sensor network with robotics. |
