Path planning in three dimensional live environment with randomly moving obstacles for viscoelastic bio-particle

Significant capabilities of atomic force microscopy (AFM) such as operating in various environments and scales made it a useful device in different operations. According to AFM abilities and applications, in this work, the path through the live environment with fixed and moving obstacles that are distributed all over the space randomly has been provided. The optimized path has been discovered in this article based on the applications mentioned above. Since for biological applications, the tool's accuracy plays an important role in success and reliability of the operation, in this article, the cost function is defined as combination of the tool's error, the maximum applied force on the tool, and the maximum deformation of the particle to be minimized. In this regard, constraints which limit the particle's motion and speed such as critical force and time and the maximum applied force have been considered. While in living environment obstacle existence is possible, fixed and moving obstacles with random profile and distribution will be considered. Routing of viscoelastic particle considering above conditions has been performed and comparison with the previous works proved the correctness of the path. The effects of different constraints have been compared using path optimization in different situations. The time of path planning for critical force and time was about 117.657, for the maximum applied force 118.240, and for all constraints together was 120.540 s which shows that the applied force constraint has been more effective than others and increases path planning time. Path planning in three dimensional live environment of HN5 cells. Consideration of viscoelasticity for biological particles. Consideration of randomly distributed stationary obstacles and moving obstacles with unknown motion profile. Minimization of tool error and particle deformation along with finding the shortest path.

Automated summary

In this study, the authors utilized the capabilities of atomic force microscopy to optimize paths in a live environment with fixed and moving obstacles. By defining a cost function and considering constraints, they were able to minimize tool error and particle deformation in biological applications. The study showed that the constraint on applied force was more effective than others and increased path planning time.