Owing to the explosive advancements in recent years in the areas of computational intelligence, material synthesis, and device integration, a new era of intelligent robotics, featuring unprecedented capabilities of sensing, actuation, and decision making, has arrived. Various newly developed robotic systems have penetrated into virtually all industrial sectors, ranging from manufacturing, energy, aerospace and naval, infrastructure, to health care and service, etc. They possess remarkably enhanced performances in terms of accuracy, adaptivity, reliability, and autonomy, and are poised to change fundamentally our modalities of working and living. The new accomplishments exemplify the collaborative efforts by academia and industry that are currently accelerating. Aiming at documenting and disseminating the progresses and identifying growth opportunities, this “Focused Section on Machine Learning, Estimation and Control for Intelligent Robotics” of the International Journal of Intelligent Robotics and Applications (IJIRA) showcases a number of recent technological achievements in the learning and control of robotic systems. It includes nine papers that share the common theme of robotic systems utilizing complex or heterogeneous data in their design and control through advanced learning and estimation techniques.