Steering Micro-Robotic Swarm by Dynamic Actuating Fields
Charlie Wang (TU Delft - Materials and Manufacturing)
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Abstract
We present a general solution for steering microrobotic
swarm by dynamic actuating fields. In our approach, the
motion of micro-robots is controlled by changing the actuating
direction of a field applied to them. The time-series sequence
of actuating field’s directions can be computed automatically.
Given a target position in the domain of swarm, a governing
field is first constructed to provide optimal moving directions at
every points. Following these directions, a robot can be driven
to the target efficiently. However, when working with a crowd of
micro-robots, the optimal moving directions on different agents
can contradict with each other. To overcome this difficulty, we
develop a novel steering algorithm to compute a statistically
optimal actuating direction at each time frame. Following a
sequence of these actuating directions, a crowd of micro-robots
can be transported to the target region effectively. Our steering
strategy of swarm has been verified on a platform that generates
magnetic fields with unique actuating directions. Experimental
tests taken on aggregated magnetic micro-particles are quite
encouraging.