sewts GmbH
2024-Present, Germany
Soft Skills:
Project Management, Agile Development, Problem-Solving, Stakeholder Communication
Tools:
GitHub, Confluence, JIRA, MS Suite
Technical Skills:
CAD, Multibody Dynamics, PLC Programming (TwinCAT 3), Prototyping, Robotics Engineering, R&D, Multibody Simulation, Electronics and Firmware Design, Robot Cell Design
Tools:
Autodesk Inventor/VAULT, GitHub, Realtime Robotics RealPlan, ANSYS, Python, GCP, IsaacSIM, Beckhoff TwinCAT3, FANUC Roboguide
VESTIS: Industrial-Grade Textile Robotics
Project Overview
VESTIS is a modular robotic platform designed to automate the handling of deformable textiles—such as garments and towels—across high-throughput industrial applications. The system integrates dual-arm cobots, real-time vision pipelines, and a scalable PLC/IPC stack to enable intelligent automation in laundries and logistics centers.
My role bridged engineering and product leadership. I shaped system architecture, led development across mechanical and control domains, and aligned technical milestones with go-to-market needs. Our goal: to deliver a production-ready robotic solution that translates breakthrough manipulation capabilities into scalable customer value.
Strategic Contributions
Defined and Delivered Robotic Platform Capabilities:
Architected and validated a modular robotic cell supporting multiple textile workflows (folding, sorting, stacking). Scoped for TRL 5 maturity and designed with industrial scalability and field-deployability in mind.Led End-Effector Strategy for Deformable Objects:
Owned gripper development for soft-material interaction. Delivered a modular end-effector system capable of single-layer textile picks with >90% success. Integrated force and tactile sensing for error recovery and adaptive behavior.Enabled AI-Driven Autonomy through Vision Integration:
Co-led integration of a proprietary 2D/3D vision stack for high-variance textile detection—supporting tasks like soiled-side sorting and seam-based pick planning. Collaborated with ML engineers to align perception outputs with motion planning constraints.Managed Full System Lifecycle from Prototype to Pilot:
Oversaw subsystem integration (cobots, conveyors, sensors, PLC), ensuring real-time coordination and safety compliance via TwinSAFE and EtherCAT. Delivered investor demos and industrial PoCs aimed at meeting throughput KPIs of 450–750 items/hour.Drove Agile Execution and Cross-Functional Alignment:
Coordinated cross-disciplinary teams (robotics, software, mechanical, and ML) using agile workflows. Owned technical delivery while maintaining alignment with roadmap, cost targets, and stakeholder goals.