An Indeterministic Vision-Based State Observer for Growing Magnetic Microrobot Motion Status Estimation

To date, untethered micro/nanorobots have attracted considerable attention in various aspects due to their unique potential for in-vivo applications such as the targeted therapy. One of the most promising types of micro/nanorobots is the class of ferromagnetic microrobots which can be efficiently actuated via gradient/rotational magnetic field generated by less costly electromagnetic coil systems. For performing successful operations, locomotion control of the magnetic microrobots is non-trivial. Modern controllers commonly require motion status-based feedback. To fully utilize those advanced approaches, motion state of one microrobot should be supplied, however it is still challenging in cases. It is noted that, during locomotion, one ferromagnetic microrobot can combine with others to form an unstructured larger one, namely growing magnetic microrobot (GMM), whose dynamic behavior keeps changing, and thus the model-based observers are never applicable. Besides, tracking and estimating states of those unstructured time-varying GMMs in complex surroundings are always challenging, especially for an uneven sampling scenario. In order to accurately estimate the GMM motion status in a complex environment via micro-vision, this study develops an indeterministic observer leveraging on the approach of discriminative correlation filter with channel/spatial reliability (CSR-DCF) and the variable-step finite-time sliding mode (FSM-V) state estimation theory. Experimental study verifies that the proposed observation scheme can effectively estimate motion states of one GMM moving in obstacle surroundings throughout.