@inproceedings{C25b,

title = {Feasibility of Nano-Acoustic Subsurface Imaging for Atomic Force Microscopy},

author = {C. J. Carlon and Y. K. Yong and A. J. Fleming},

url = {https://www.precisionmechatronicslab.com/wp-content/uploads/2025/11/Feasibility_of_Nano-Acoustic_Subsurface_Imaging_for_Atomic_Force_Microscopy.pdf},

doi = {10.1109/ICM62621.2025.10934819},

isbn = {979-8-3315-3389-2},

year  = {2025},

date = {2025-02-28},

urldate = {2025-02-28},

booktitle = {IEEE International Conference on Mechatronics },

address = {Wollongong, Australia},

abstract = {The feasibility of a new imaging regime for sub-surface Atomic Force Microscopy (AFM) is investigated using synthetic aperture focusing technique. This technique uses two Atomic Force Microscopy (AFM) probes to emit acoustic pulses and sense echoes. Unlike other existing subsurface AFM methods, Nano-Acoustic Subsurface AFM (NASAFM) provides cross-sectional images of a sample below the surface with depth information in the nanometre scale. In order to determine the best resolution, two ideal wideband AFM probes are considered in simulation. The results show that a 20 ps pulse with a bandwidth of 330 GHz was able to resolve two 50 nm discs, 500 nm below the surface, separated by 340 nm. Future work is needed to understand the relation between resolution and bandwidth, the optimal imaging parameters, and the sensing technique.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Stanwell2025,

title = {Feasibility of Nano Electrical Resistive Tomography for Subsurface Atomic Force Microscopy},

author = {B. J. Stanwell and Y. K. Yong and A. J. Fleming},

url = {https://www.precisionmechatronicslab.com/wp-content/uploads/2025/11/Feasibility_of_Nano_Electrical_Resistive_Tomography_for_Subsurface_Atomic_Force_Microscopy.pdf},

doi = {10.1109/ICM62621.2025.10934851},

isbn = {979-8-3315-3389-2},

year  = {2025},

date = {2025-02-28},

urldate = {2025-02-28},

booktitle = {IEEE International Conference on Mechatronics},

address = {Wollongong, Australia},

abstract = {This article investigates the feasibility of using a dual-cantilever atomic force microscope for imaging the electrical properties of a sample below the surface. Principles from macro-scale electrical resistive tomography are adapted to utilize measurements from a dual-probe atomic force microscope. A deep-learning method is employed to perform the inversion process and construct the tomography. Simulation results demonstrate that electrical resistive tomography is possible at the nanometre scale but improvements to the inversion algorithms are needed before moving to experimental applications.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{nokey,

title = {Data-Driven Inverse Control of Pneumatic Soft Robotic Actuators with On-Off Valves: Simulated Performance},

author = {T. R. Young and Y. K. Yong and A. J. Fleming},

url = {https://www.precisionmechatronicslab.com/wp-content/uploads/2025/11/Data-Driven_Inverse_Control_of_Pneumatic_Soft_Robotic_Actuators_with_On-Off_Valves_Simulated_Performance.pdf},

doi = {10.1109/ICM62621.2025.10934841},

isbn = {979-8-3315-3389-2},

year  = {2025},

date = {2025-02-28},

urldate = {2025-02-28},

booktitle = {IEEE International Conference on Mechatronics},

address = {Wollongong, Australia},

abstract = {This article describes a data-driven control method for fast and accurate pressure regulation of pneumatic soft robotic actuators with on-off valves. Due to the non-linearity and binary control input, linear controllers are not ideal for pressure regulation as they must be tuned conservatively, which results in a slow transient response. Alternatively, non-linear methods can provide a faster response time but are complicated by the need for an accurate model. This article proposes an inverse control approach, where the control action is parameterized by the valve on-time, and the system output is the cumulative change in pressure after the control action is complete and all system transients have decayed. This approach eliminates the need for a dynamic model and results in a small space of input-output combinations that can be measured from a calibration experiment. The result is a non-linear inverse controller that does not require a dynamic model. The proposed method is compared in simulation to a hysteresis controller with three different valve orifice diameters. Significant improvements to the pressure regulation and valve lifetime are observed. This method is expected to find applications in soft robotics where fast step changes and dynamic trajectories are required.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}