Target finding and obstacle avoidance algorithm for microrobot swarms

Advances in the development of nanotechnology have led to microrobots applications in medical fields. Drug delivery is one of these applications in which microrobots deliver a pharmaceutical compound to targeted cells. Chemotherapy and its side effects can then be minimized. Two major constraints, however, must be considered: the robot's onboard energy supply and the time needed for drug delivery, which are related to the travel distance of microrobots. Furthermore, a microrobot must avoid biological restricted areas which we treat as obstacles in the path. The main objectives of this work are to find optimal paths to targeted cells and avoid collision with obstacles in the paths. In this study, we control motion of microrobots based on the concept of swarm intelligence. Artificial Bee Colony, the swarm-based optimization method, is employed to implement the collision detection and the boundary distance detection modules. The offline path distance optimization approach is also employed to improve the path planning results. Numerical experiments have been conducted using various obstacle environments that confirm that the proposed approach is successful in avoiding obstacles and optimizing the distance traveled to reach the target.