Alexander Kalis
Industrial Engineer & Industrial Robotics Specialist
Industrial Engineer passionate about bridging the gap between heavy industrial hardware and advanced intelligent software. I specialize in developing robust robotic control systems, leveraging ROS2, C++, Python, and containerization technologies to modernize platforms like KUKA, FANUC, and ABB.
My focus lies in solving complex automation challenges—from real-time motion planning to AI-driven vision and scalable deployment architectures—optimizing autonomous systems for the next generation of industrial manufacturing.
Core Expertise & Technology Stack
Automation & Industrial Control
- Robot Programming
KUKA, FANUC, ABB - PLC / HMI / SCADA
Siemens, Beckhoff, Omron - Vision Systems
Keyence, Photoneo, Zivid, Cognex | 2D/3D Machine Vision, LiDAR, Sensor Fusion - Motion Control
Advanced Kinematics, Control, & Motion Planning
Robotics Software & Middleware
- Core Languages
C++, Python, C, C#, LUA, Java - Middleware
ROS2, DDS/RTPS Protocols, Real-Time Data, RoboDK API - Data Analysis & Computing
Machine Learning, Scientific Computing, Data Science
Real-Time Systems & Deployment
- Deep Linux Systems
Linux Enthusiast & AUR Contributor - Shell Scripting
Bash, Zsh, System Automation - Real-Time OS
RTOS Implementation and Kernel Tuning - DevOps / Version Control
Advanced Git, CI/CD Workflows, Docker, Kubernetes
Featured Projects
HARTU: Intelligent Mobile Manipulation Platform
Advanced robotics platform combining KUKA iiwa with autonomous mobile robotics for flexible manufacturing. Features edge computing with NVIDIA Jetson, AI-powered 3D vision for intelligent grasping, containerized deployment for scalable updates, and sophisticated path planning for dynamic environments.
- Technology Stack: ROS2 (C++ & Python), NVIDIA Jetson Edge Computing, Docker Containers, Zivid 3D Camera, AMR (Autonomous Mobile Robotics).
- Focus: Real-time high-performance computing on edge devices, AI-driven image processing and grasping point algorithms, containerized software deployment for consistent runtime environments, autonomous mobile platform path planning, and seamless ROS2 integration with industrial robots.
- Outcome: Fully integrated mobile manipulation system with intelligent object recognition, adaptive grasping, and autonomous navigation enabling flexible production scenarios.
Key Technologies
GitHub Repository
Aleynikovich/iiwaTOFASZINKERREKA: Advanced Industrial Automation System
Comprehensive KUKA robot automation system featuring advanced 3D vision, intelligent bin-picking, and zinc surface treatment for industrial screw manufacturing. Integrates machine vision with custom UI for seamless operation and process control.
- Technology Stack: KUKA KRC, MVTec HALCON 3D Vision, C# (.NET), XAML UI Framework, PROFINET MS, Industrial Laser Integration.
- Focus: Custom bin-picking algorithm for intelligent object recognition, zinc coating process automation for screw anticorrosion treatment, and modern UI development for operator control and process monitoring.
- Outcome: Production-grade automation system with intelligent vision-guided pick-and-place, precision surface treatment, and intuitive operator interface delivering significant throughput improvements.
Key Technologies
GitHub Repository
Aleynikovich/ZinkerrekaSmart Pal: AI-Driven Adaptive Palletizing System
Intelligent KUKA robot palletizing system enhanced with machine learning capabilities for dynamic production optimization. Multilayered architecture deployed across distributed robotic cells using containerization for consistent behavior. Features adaptive recipe generation that learns from production patterns to automatically create and optimize palletizing sequences on the fly.
- Technology Stack: KUKA KRC (Robot Control Language), Kubernetes for Multi-Cell Deployment, Machine Learning Algorithms, Production Data Analytics, Industrial I/O Configuration.
- Focus: Distributed deployment architecture enabling synchronized operation across multiple robotic cells in matrix production layout. ML-powered production recipe generation adapting to real-time requirements, intelligent palletizing pattern optimization, predictive maintenance, and automated cycle time reduction through data-driven decision making.
- Outcome: Self-optimizing palletizing system deployed across multiple cells that generates custom recipes automatically, dramatically reducing setup times and increasing operational flexibility while maintaining production quality and consistency across the distributed fleet.
Key Technologies
GitHub Repository
Aleynikovich/errekaSmartPalSYSIQ: AI terminal integration
Comprehensive software library for dedicated AI guided command line terminal applications in automation workflow. Provides reusable components and tools to streamline development of robust, high-performance terminal-based solutions for system integration, quality assurance, and communication protocols.
- Technology Stack: C++, Python, Modern Software Architecture, Cross-Platform Compatibility, Modular Design Patterns.
- Focus: Reusable components for system integration, quality assurance frameworks, standardized communication protocols, and development tools that accelerate industrial automation projects.
- Outcome: Production-tested library reducing development time through proven patterns, comprehensive documentation, and modular architecture supporting rapid prototyping and deployment.
Key Technologies
GitHub Repository
Aleynikovich/sysiqLet's Connect
I'm open to discussing engineering challenges, industrial automation opportunities, or research collaboration.
© Alexander Kalis.