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Abstract Swimming micro/nanorobots attract considerable attention due to their considerable promises in various fields ranging from environmental remediation to biomedicine. However, the control system for optimal trajectory and precise localization is an exciting yet challenging for the existing swimming micro/nanorobots. Researchers have used different actuation systems allowing multiple degrees of freedom to actuate swimming microrobots with various motion control methods from well‐controlled physicochemical processes to achieve autonomous movement along the gradient of various chemical or physical fields. Furthermore, with the advance of intelligent technology, machine learning strategies have been considered for intelligent control of swimming microrobots. In this paper, we summarized directly manual control and autonomous tactic motion of swimming micro/nanorobots. The application of reinforcement learning in controllable motions of swimming microrobots was also elaborated.