Research and Documentation of My Work in Robotics and Computing

Robotic Sensor Module Design

Tactile Sensing Artificial Fingertip for Prosthetics and Humanoids

I developed a high-density tactile fingertip capable of sensing pressure and vibration in a compact form factor. It was designed for humanoid robotic hands and can also be applied in prosthetic fingers, developed as part of my research in tactile sensing.

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High-Density Tactile Sensing Artificial Fingertip for Humanoids and Prosthetics

This project focuses on the design and development of a high-density tactile fingertip module intended for humanoid robot and prosthetic hand applications. The module is capable of measuring pressure exerted on its surface through 22 individual pressure sensors distributed across the fingertip area. It is developed using Flexible Printed Circuit Board (Flex-PCB) technology.

In this project, an origami technique is employed to fold a flat, paper-like flexible tactile sensing module into a three-dimensional shape that mimics the form of a human fingertip. Sensor data acquisition is handled by an onboard 32-bit, low-power microcontroller, and the module communicates using the SPI protocol.

In this project, an origami technique is employed to fold a flat, paper-like flexible tactile sensing module into a three-dimensional shape that mimics the form of a human fingertip. Sensor data acquisition is handled by an onboard 32-bit, low-power microcontroller, and the module communicates using the SPI protocol.

The development of this module presented a number of challenges, particularly in mechanical design and electronics. Prior to this project, I had limited experience with mechanical Computer-Aided Design (CAD). I had to learn how to design both mechanical structures and electronic schematics, as well as manage the manufacturing and integration processes.

Despite these challenges, a functional prototype of the tactile fingertip was developed. While the current version is not yet optimized for production, it is capable of capturing tactile data. Ongoing work includes further optimization of the design, data collection, and analysis.

The dimensions of the fingertip module closely match those of a typical human fingertip, enabling applications in humanoid robots and prosthetic systems.

CAD Model

Figure 2: The CAD model on the left illustrates the structural design and assembly of the high-density tactile fingertip module. It was created using Siemens Solid Edge, leveraging the sheet metal environment to model the foldable geometry of the flexible PCB. The part environment was used to design and integrate additional components, including pressure sensors and the onboard microcontroller.

Board Layout

The schematics and board layout of the tactile fingertip module were designed using Autodesk Eagle EDA. It was a challenging task, as a large number of vias had to be managed within a very small area. The board layout includes approximately 218 vias on a two-layer flexible PCB, with dimensions around 32 mm × 74 mm.

Figure 3: Board layout of the tactile fingertip module.

Fully Populated Tactile Fingertip Module

The tactile fingertip module is manufactured using 2-layer flexible PCB technology with a thickness of 0.11 mm. After fabrication, surface-mount technology (SMT) is used to populate the electronic components. Figure 4 depicts the fully populated tactile fingertip flexible PCB placed next to a 10-cent coin, highlighting the size difference and the complexity of the design.

Figure 4: Fully fabricated and populated tactile fingertip module in flat form factor.

Origami

A technique called origami, a traditional Japanese art of folding paper to form intricate shapes, is applied here to transform the flat version of the flexible tactile fingertip module into a 3D shape resembling a fingertip. Although origami is a complex art and I don't have much expertise in it, I attempted a simplified version to apply the technique as best as I could. The figure below shows the fingertip after being folded using origami techniques, including both the top (Figure 5a) and bottom (Figure 5b) views. The bottom view represents the fleshy part of the fingertip.

Figure 5: Top (a) and Bottom (b) views of the tactile fingertip module folded into a 3D humanoid fingertip-like shape using origami techniques.

Tactile Fingertip on a Human Finger

Figure 6: Shows the high-density tactile fingertip module mounted on a human finger. This demonstration is for illustrative purposes only. While the module is designed for integration into a humanoid robot hand, I did not have access to the robot hand toward the end of the project. I plan to update this demonstration with a robotic hand implementation in the near future.

Future Work

Further work on data collection, analysis, and system optimization is planned. In future updates, I aim to include additional documentation such as:

Detailed experimental results
Data analysis and sensor performance evaluations

This project will likely continue to evolve as time allows. At the moment, my availability is limited due to involvement in other work. While I have clear plans for improvements, progress will depend on available time."

I haven't published the data, schematics, or full documentation yet, as I believe the project isn’t complete enough to share publicly. Once it reaches a point I consider satisfactory, I will make those materials available.

AI - Computer Vision

AI Traffic Monitoring Application with Object Detection and Counting

This project uses CNN-based object detection to count vehicles crossing a traffic signal and display the number of vehicles detected, categorized by type, in a tabular format. The application uses a pretrained YOLO (You Only Look Once) model for object detection.

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AI - Computer Vision

Handwritten Digit Recognition App Using CNN

An application that recognizes handwritten digits using a Convolutional Neural Network (CNN). The model is trained on the MNIST dataset and integrated into a user-friendly GUI built with Python.

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Handwritten Digit Recognition Application using CNN

A simple and intuitive application that recognizes handwritten digits using a Convolutional Neural Network (CNN). The model is trained on the MNIST dataset and deployed with a user-friendly PyTkinter GUI.

Getting Started

To get started with the Handwritten Digit Recognition App, follow these steps:

Clone the repository
Navigate to the project directory
Install the required dependencies
Run the application

Clone the Repository


git clone https://github.com/neoviki/ai.vision.handwritten.digit.recognizer.cnn.mnist.git
cd ai.vision.handwritten.digit.recognizer.cnn.mnist

Install Dependencies


chmod +x install.dependencies.sh
./install.dependencies.sh

Run the Application


chmod +x run.app.sh
./run.app.sh

Reference


@article{lecun2010mnist,
  title={MNIST handwritten digit database},
  author={LeCun, Yann and Cortes, Corinna and Burges, CJ},
  journal={ATT Labs [Online]. Available: http://yann.lecun.com/exdb/mnist},
  volume={2},
  year={2010}
}

For more details on this project, visit https://github.com/neoviki/ai.vision.handwritten.digit.recognizer.cnn.mnist

Computer Networks - IoT

IoT Data Transmission Suite

An IoT Data Transmission Suite with a server daemon and client library, designed for IoT applications. Traffic is transmitted over the HTTP/HTTPS protocol. It supports homegrown plant monitoring and vehicle status tracking, offering a cost-effective alternative to MQTT for lightweight, low-traffic communication. This suite is ideal for simple IoT ecosystems where frequent or intensive data exchange is not required.

GitHub

Embedded Controller Module

Tactile Controller

A 32-bit embedded controller module developed to efficiently retrieve and process tactile sensor data.

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TUI - Terminal User Interface

Terminal CSV Editor

A Linux terminal-based CSV editor written in Go. It features a Terminal UI (TUI) for viewing and editing CSV files and is fully keyboard-driven - no mouse required.

GitHub

Sensor Module Design

Tactile Sensing Module with a Dense Arrangement of Sensors

This tactile sensing module was developed to evaluate the application of closely arranged barometer sensors in tactile sensing.

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Other Projects

List of Other Projects I have Worked On

I’ve worked on a variety of projects based on my interests and the challenges I encountered along my journey. These projects span across AI, Computer Networking, Linux, GUI, Terminal tools, as well as Robotics and Electronics. I’ve documented and published them on GitHub. This section includes a list of those projects along with their corresponding GitHub URLs.

More Info GitHub

List of Projects

I've had the opportunity to work on projects across a range of fields, including telecom, vehicle telematics, IoT, computer vision, and robotic sensor design - covering areas such as computer science, electronics, and robotics. These projects were practical solutions to challenges I encountered in both day-to-day computing and industry environments. They include Linux utilities, drivers that optimize and streamline personal and industrial workflows, Artificial Intelligence driven applications and command-line tools using `awk`, `sed`, and regex for data splitting, filtering, manipulation, and interpretation. I've also developed C/Python libraries and packages, as well as custom hardware modules such as tactile sensors for robotic sensing.

Below is a list of selected projects, all of which I've published on GitHub.

Nr	Project Details	Reference
1	ai.vision.realtime.traffic.monitoring	Link
2	flexible.tactile.sensing.module.dual.sensors	Link
3	tactile.controller.module	Link
4	ai.vision.traffic.monitor.app	Link
5	ai.vision.handwritten.digit.recognizer.cnn.mnist	Link
6	ai.vision.image.classifier.cnn.cifar10	Link
7	ai.ml.classification.knn	Link
8	ai.vision.face.detector	Link
9	explainable.ai.evalution.app	Link
10	linux.over.the.air.app.updater	Link
11	linux.tcp.port.tunneler	Link
12	linux.remote.debugger.utility	Link
13	linux.app.installer.utility	Link
14	linux.embed.dir.to.bash.script	Link
15	linux.rpi.samba.file.share	Link
16	linux.rpi.vnc.server	Link
17	linux.rpi.wifi.access.point	Link
18	linux.wifi.monitor	Link
19	linux.detect.usb.flash.drive	Link
20	mesos.distributed.cluster.deployer	Link
21	proxmox.virtualization.cluster.deployer	Link
22	ceph.distributed.storage.cluster.deployer	Link
23	compress	Link
24	versionsnap	Link
25	graphical.interface.grid.eye.sensor.electron	Link
26	graphical.interface.gyroscope.sensor	Link
27	graphical.interface.robotic.gripper	Link
28	graphical.interface.serial.monitor	Link
29	iot.data.exchange.suite	Link
30	eagle.library.pic32mm0256gpm036.uqfn.40pin	Link
31	eagle.library.pic32mm0256gpm028.uqfn.28pin	Link
32	arduino.AMG8833.grid.eye.sensor	Link
33	arduino.Bosch.BMP384.pressure.sensor	Link
34	arduino.VL6180X.time.of.flight.distance.sensor	Link
35	arduino.esc.controller	Link
36	audio.joiner	Link
37	audio.multiplier	Link
38	video.splitter	Link
39	video.to.gif	Link
40	automate.transaction.on.ebay	Link
41	crop.image	Link
42	docker.wrapper.commands	Link
43	gps.coordinates.renderer.osm	Link
44	lib.json	Link
45	lib.xml.parser	Link
46	ipc.filelock	Link
47	ipc.messenger	Link
48	ipc.shared.memory	Link
49	mac.osx.tabrun	Link
50	netcopy	Link
51	rand.file.tagger	Link
52	terminate	Link
53	uscreen	Link
54	website.backup.and.restore.utility	Link
55	html.ui.generator	Link
56	ui.python.tkinter.wrapper	Link

About Me.

I am Viki (VN), a freelance software architect experienced in building solutions involving software systems, artificial intelligence, computer clusters, and embedded systems. I have designed solutions in industries and domains including Automotive, IoT, Computer Networking, Cloud Technologies, and Robotics. I hold a Master's degree in Computer Science and Robotics from Germany. My GitHub repository [ Ref] and this website document the solutions I have developed until now.

Expertise

I have built software applications and embedded solutions from scratch and improved existing systems. My work includes the design and development of embedded robotic sensor modules [Ref: 1, 2, 3, 4]; Artificial Intelligence applications [Ref: 1, 2, 3, 4]; applications for embedded systems [Ref: 1, 2]; Linux applications and libraries [Ref: 1, 2, 3, 4]; bare-metal and virtual computing cluster infrastructure deployment and management [Ref: 1, 2, 3]; distributed storage infrastructure deployment and management [Ref: 1, 2, 3]; IoT solutions [Ref: 1, 2]; and containerized Docker applications [Ref: 1, 2]; One of the solutions I developed is currently used in around 10,000 automotive devices in Europe [Ref].

Skills

I have wide experience in computing and its interdisciplinary areas, including sequential, concurrent, and parallel programming; computer networking; Linux-based application development[Ref: 1, 2, 3, 4, 5, 6], and Linux device-driver development; Linux boot-time optimization; Application containerization with Docker [Ref: 1, 2]; AI model integration and AI application development (CNN, XAI) [Ref: 1, 2, 3, 4]; and embedded firmware development. I have developed solutions involving OSI communication protocols, including TCP/IP, MQTT, and SSH [Ref: 1, 2], as well as hardware interfaces such as SPI and I²C [Ref: 1, 2, 3, 4]. Alongside software development, I have hands-on experience designing embedded sensor modules and controllers using KiCAD and Eagle [Ref: 1, 2, 3, 4], and I also work with CAD tools such as Solid Edge and FreeCAD [Ref].

Professional Experience

I have more than 14 years of experience in the software industry, including nearly a decade at a well-known computer networking company based in California. For over five years, I have worked as a consulting software architect and manager, supporting clients across Europe and the UK. I have collaborated with and led engineers from diverse cultural and professional backgrounds, including teams from France, the UK, Russia, and South Asia.

Achievements

One of my most demanding and rewarding achievements is the development of a high-density tactile fingertip module [Ref] from scratch for humanoid robots. This project involved complete CAD modeling, electronics design, and embedded firmware development, giving me a full understanding of building a solution across three areas: computing, electronics, and mechanical design. Beyond engineering, the project taught me how to work with manufacturers, optimize costs, handle local taxation, and manage all practical steps required to produce the final sensor module.

Home Lab

I maintain a home lab equipped with essential tools, including a small LAN rack with interconnected Linux bare-metal clusters running virtual machines and Docker containers, embedded GPU modules for AI experiments, and general-purpose embedded microcontroller and microprocessor modules based on ARM, ATMEL, PIC and STM. I also have embedded hardware assembly and testing equipment, such as a soldering station, surface-mount tools, logic analyzer, oscilloscope, and a 3D printer.

In my home lab, I have created over 40 open-source projects, ranging from embedded hardware and AI applications to over-the-air update utilities, Linux tools, and sensor modules. A few of the libraries and solutions I developed are still in use in the field by my previous employers. All of these projects are documented on my GitHub[Ref].

Tools I Use Regularly

For software development, I primarily write in C [Ref: 1, 2, 3, 4], Python [Ref: 1, 2], and Bash [Ref: 1, 2, 3, 4, 5, 6], and have experience with Rust, Go [Ref], AWK, PHP [Ref: 1, 2], and JavaScript [Ref: 1, 2, 3, 4]. For embedded hardware module design, I work with Eagle and KiCAD [Ref: 1, 2, 3, 4]. For network protocol debugging, I use Wireshark and logic analyzers, and for Linux application crash analysis, I use GDB. For CAD modeling, I work with Solid Edge and FreeCAD[Ref]. I have good hands-on experience with all of these tools.

Contact Me.

You can get in touch with me at hello@viki.design