Design and Implementation of a Motion Control Architecture for WormPicker 2.0 Robotic System

Abstract

Genetic research relies on model organisms like C. elegans, microscopic nematodes valued for their genetic simplicity and short lifecycles. Researchers must physically transfer these worms between experimental conditions, a process traditionally performed manually with wire picks - creating significant bottlenecks in experimental throughput. Automation is critically needed for high-throughput studies. An integrated system combining a 6-axis robotic arm, motorized microscope, and AI-driven machine vision has been developed to address this challenge, known as WormPicker 2.0. This research presents the design and implementation of a comprehensive motion control architecture for WormPicker 2.0's Yaskawa GP4 robotic arm, enabling autonomous execution of complex protocols. The developed software architecture follows a layered design pattern that transforms high-level experimental commands into precise robotic movements. At its core, the system employs ROS2 and MoveIt2 frameworks for motion planning and execution. It features a modular structure that separates concerns across five layers: interface, command processing, task generation, motion planning, and execution. Key technical contributions include a command parser that processes multi-parameter instructions. The system also incorporates a task generation framework that dynamically creates motion sequences from workspace configurations. Additionally, it features a calibration system that maps between digital design models and physical workspace coordinates, along with multiple interfaces for remote network access and direct command-line control. This motion control system enables WormPicker 2.0 to achieve a transfer rate of 13 animals per minute (4 times improvement over previous implementations) while maintaining precise navigation across 250 plates in a compact footprint. By automating worm manipulation, this work significantly enhances research capabilities for genetic screens, aging assays, drug response studies, and behavioral analysis. The modular software architecture provides a foundation for future enhancements, moving closer to a general-purpose tool for C. elegans laboratories that dramatically increases experimental throughput and reproducibility.No embargoAcademic Major: Biomedical Engineerin