Equipping micro‐/nanoscale colloidal robots with artificial intelligence (AI) such that they can efficiently navigate in unknown complex environments can dramatically impact their use in emerging applications such as precision surgery and targeted nanodrug delivery. Herein, a model‐free deep reinforcement learning algorithm is developed that trains colloidal robots to efficiently navigate in unknown environments with random obstacles. A deep neural network architecture is used that enables the colloidal robots to mimic animal navigation decision‐making by directly processing raw sensor input and decomposing long‐range navigations to short‐range ones. The trained robot agents learn to make navigation decisions regarding both obstacle avoidance and travel time minimization, based solely on local sensory inputs without prior knowledge of the global environment. Such agents with biologically inspired mechanisms can acquire competitive navigation capabilities in large‐scale, complex environments containing obstacles of diverse shapes, sizes, and configurations. Herein, the potential of AI to enable colloidal robots in extensive applications is illustrated.

We report confocal laser scanning microscopy (CLSM) measurements, Monte Carlo (MC) simulations, and an analytical model of the assembly of three dimensional (3D) equilibrium colloidal crystals within quadrupole electrodes on microscope cover slip surfaces. Micron sized fluorescent silica colloids in an index matching dimethylformamide (DMF) medium enable three dimensional CSLM imaging to measure particle coordinates. By matching density profiles from CSLM measurements and MC simulations, we obtain electrostatic, dipole–field, dipole–dipole, and gravitational potentials that accurately capture the three dimensional microstructure and morphology. We also report analytical density profiles with fluid–solid coexistence by balancing gravitational and electric field mediated compression against local osmotic pressure, which agree with CSLM and MC results. These results provide fundamental information on the assembly of three dimensional equilibrium colloidal crystals in the presence of multiple external fields and with coexisting inhomogeneous fluid and solid phases.