COGNITIVE_OS_LOADED // DEEP_DIVE_MODE

Yash Tomar

Multidisciplinary Engineer

Working at the intersection of software, robotics, sensing, and intelligence.

// Consciousness Core Integration

I design and build cyber-physical systems, autonomous robotics interfaces, and intelligent automation layers. Combining full-stack web architectures with low-level robotics frameworks, I create high-performance systems that bridge the physical and digital worlds.

// Core Parameters

Current RoleR&D Software & Robotics
Focus AreasVedic Geometry & Jarvis HUD
LocationIndia [UTC +5:30]
Neural FocusROS2 / local LLMs / LiDAR
QUANTUM_STATEψ = |01⟩ + |10⟩

// 02. Cyber Physical Systems

Engineering Nodes

sensors // Real-time 3D point-cloud spatial analysisSENSORS

LiDAR Stockpile Volume Estimation System

A high-precision industrial system that captures LiDAR point clouds, filters noise, reconstructs surfaces, and calculates bulk material volumes in real time.

  • Processes raw LiDAR telemetry using Open3D and ROS2 filtering pipelines.
  • Implements Delaunay Triangulation and voxel grid downsampling to model complex material surfaces.
  • Exposes REST APIs via FastAPI and serves 3D visualizations in WebGL for control rooms.
  • Maintains measurement accuracy within a 2.5% margin of error compared to manual surveys.
Accuracy
97.5%
Scan Time
< 4s
Cloud Points
500k+
ROS2PythonOpen3DFastAPIThree.jsLiDAR
sensors // Cellular telemetry outdoor robot platformSENSORS

Autonomous IoT Rover System

An autonomous outdoor mobile robot engineered for environmental telemetry, incorporating GPS waypoint navigation, collision avoidance, and remote cellular control.

  • Designed and manufactured custom rover chassis integrated with Raspberry Pi and motor controllers.
  • Deployed ROS2 navigation nodes mapping ultrasonic, infrared, and GPS telemetry.
  • Engineered an IoT remote dashboard showing real-time GPS paths and battery health over cellular networks.
  • Configured camera streams using WebRTC for ultra-low latency teleoperation.
Latency
120ms
Range
Unlimited (4G)
Battery Life
4 Hours
Raspberry PiROS2PythonC++WebRTCMQTTIoT
ai // Local LLM workspace agent and commit analyzerAI

AI-Powered Developer Growth Analyzer

A productivity application that hooks into local git repositories to analyze commit velocity, code structures, and refactoring patterns using local LLMs.

  • Interfaces with Ollama and Qwen/Llama models locally to respect code privacy.
  • Extracts AST (Abstract Syntax Tree) differences from git diffs to categorize developer activity.
  • Generates automated, interactive skills-growth roadmaps and highlights syntax hotspots.
  • Implements Vector Embeddings using ChromaDB for semantic code search within history.
Model
Llama 3 (8B)
Index Speed
100 commits/s
Privacy
100% Local
Next.jsFastAPIPythonOllamaChromaDBTailwind v4
ai // Agentic workflow automation with zero cloud dependencyAI

Local LLM Automation Engine

An enterprise automation engine that parses local document stores, executes complex chains of actions, and integrates with internal tools using agentic workflows.

  • Built using LangChain and FastAPI to process thousands of internal text files and PDFs.
  • Features a highly interactive drag-and-drop workflow editor built with React Flow.
  • Implements semantic caching to reduce redundant LLM inference passes by 30%.
  • Includes automated fallback routines when local hardware exceeds VRAM capacities.
Response
< 1.2s
Cache Hits
32%
Embeddings
BGE-Large
ReactPythonLangChainOllamaFastAPIReact Flow
logic // Config-driven robotics OS setup pipelinesLOGIC

Raspberry Pi + ROS2 Infrastructure Suite

A set of automated deployment configurations and lightweight microservices to turn any Raspberry Pi into an immediate ROS2 compute node.

  • Created customized Docker configurations optimized for ARM64 architectures.
  • Developed lightweight C++ ROS2 nodes to bridge GPIO controls and sensor reads to the DDS network.
  • Built automated shell tooling to configure real-time kernel patches (RT-PREEMPT) on Raspberry Pi OS.
  • Implemented automatic discovery scripts to let new nodes self-register with a centralized dashboard.
Setup Time
5 Mins
Kernel Jitter
< 15µs
Footprint
120MB RAM
DockerROS2BashC++Raspberry PiLinux RT

// 03. Algorithmic Capacities

Capability Matrix

01.ROBOTICS & HARDWARE

ROS2
90%
LiDAR Systems
85%
Raspberry Pi
92%
Embedded Systems
80%
Computer Vision
85%
IoT Platforms
88%

02.SOFTWARE & BACKEND

Python
95%
C++
75%
FastAPI
90%
Flutter
85%
Next.js
90%
TypeScript
88%

03.AI & INTELLIGENCE

Local LLMs (Ollama)
85%
LangChain
80%
Vector Databases
80%
Open3D / Point Cloud
85%

// 04. Long Term Memory Store

R&D Timeline

2024 - Present

Robotics & Software Developer

Research Lab / Freelance IoT Solutions
  • Designed and implemented real-time LiDAR-based stockpile volume estimation systems with custom 3D point cloud pipelines.
  • Created decentralized micro-controller networks using ROS2 and Raspberry Pi for autonomous robotic control.
  • Built full-stack control dashboards in Flutter and Next.js, displaying high-frequency telemetry data over WebSockets.
2023 - 2024

Research Contributor

Academic & Applied R&D
  • Co-authored research contributions focused on computer vision applications in autonomous vehicle pathfinding.
  • Optimized local LLM automation systems to ingest and index research papers, reducing literature review times by 40%.
  • Developed IoT telemetry modules deployed in agricultural rovers and environmental monitoring systems.

PUBLICATIONS

2024
Contribution to LiDAR-Based Volume Estimation Methods in Bulk Logistics
Y. Tomar, et al.
International Journal of Applied Robotics and Automation Research
2023
Optimal Pathfinding for Micro-Rover Platforms in Semi-Structured Environments
Y. Tomar
Robotics Sensing and Autonomous Systems Workshop
Access paper

CERTIFICATIONS

ROS2 Robotics Developer Certification
ConstructSim Robotics
2024
Deep Learning Specialization
DeepLearning.AI
2023
Advanced Embedded Systems and IoT Architectures
Coursera / UC Boulder
2023

// 05. YouTube Broadcast Network

Media Telemetry Hub

@yashtomar

Official Broadcast Channel

Core ContentRobotics & IoT
Video LogsR&D Telemetry
Channel TypeEducational
Subscribe to Channel
// Channel Overview & Mission

Bridging Physical Assemblies and Edge Intelligence

On my YouTube channel, I broadcast live build logs, software architectures, and hardware testing runs for autonomous robotics and IoT projects. By sharing telemetry analysis, CAD assemblies, and ROS2 configurations publicly, I seek to help developers build complex cyber-physical structures from scratch.

ROS2 / LiDAR Builds

Step-by-step walkthroughs of point cloud estimation architectures and micro-rover navigation setups.

IoT & Dashboard Integrations

Tutorials on connecting micro-controller arrays with real-time web telemetry dashboards using WebSockets.

Latest: LiDAR Volume Estimation R&D logWatch Video Broadcasts

// 05. Socket Establishment

Establish Connection

// Connection Parameters

Have a deployment roadmap, custom LiDAR telemetry project, or want to integrate advanced edge intelligence into your robotic assemblies? Ping me.

Status: Ready to receive sockets

// Message pipeline parameters