Abstract
Robots are used frequently nowadays to reduce the human effort due to its efficient capability and performance. However, interaction with human-friendly environment is needed to integrate the robot accurately. Recently, robotic vision plays an important role in the real-world phenomenon to achieve this goal. This is because robotic vision has the capability to identify and determine the accurate positions of all related objects within the working area of the robot. In robotic vision, images are used as input, which analyzes the content of images. These have been used for the output of the system based on the criteria of image analysis, image transformation, and image understanding. Hence, the system may be able to capture the related information using the motion of the objects. And it updated this information for verification, tracking, acquisition, and extractions of images to adopt in the database. The main objective of this work is to enable the algorithm to understand the visual world. In order to achieve the goal, we have proposed an algorithm which is based on computer vision theories. Experiments have been performed on real-world image which shows our algorithm has better performance.
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Khan, A., Li, JP., Malik, A., Yusuf Khan, M. (2019). Vision-Based Inceptive Integration for Robotic Control. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 898. Springer, Singapore. https://doi.org/10.1007/978-981-13-3393-4_11
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DOI: https://doi.org/10.1007/978-981-13-3393-4_11
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