This chapter discusses the synergy of machine learning and computer vision in robotics and their prominence. The discourse explores the concept of image processing among others as weight and density are explained in sub-processes that include acquisition, preprocessing, feature extraction, and object recognition. These processes together allow the robot to operate or act with intelligence within the surrounding environment. The document especially emphasizes various prominent uses of robotics like auto-navigation, skilled handling of objects, and precise cooperation with human colleagues in the near vicinity with particular reference to efficiency enhancement in time and productivity within different industry sectors. Moreover, the treatise also analyses future trends that may influence the world to a significant extent including robot perception, artificial intelligence, multi-sensory training, continual learning, and explainable AI along with the future prospectus of edge computing. All of these trends stress the possibility of innovative change in the given domain, increasing the option-to-move and real-time decision-making possibilities. These are self-governance, aesthetics and structure, spread, compatibility, flexibility, maintainability, and the question of the morality of autonomous systems. The transparency of machine learning models and the trust and dependability in robotics that we are trying to develop will form a basis for solid and effective relationships between humankind and robots.