Astrofin+ – Tri-Arm Visual Tracking System for a Golden Fish Motion
Date
Nov 2024 - Jan 2025
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Location
London
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Project type
Electronic music art and robotic engineering
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Role
Designer & Assembler of the Robotic Arm System
Developer of the Visual Tracking System Software
This installation visualizes a fish navigating the cosmos, symbolizing exploration through motion and sound. On the surface, it presents a poetic journey; beneath, it challenges the role of human performers in electronic and audiovisual art. Can a non-human ensemble—fish, AI, and code—match or surpass human expressivity?
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The work also explores the evolving relationship between carbon-based life and digital existence. Through particle visuals and interactive systems, it reflects on how digital technologies reshape identity, consciousness, and performance. It invites reflection on self-expression, human-machine interaction, and our place in a symbiotic digital future.
I built this system from the ground up, integrating a robust visual tracking module with a six-axis robotic arm. Using an Arduino-based control board paired with the OpenMV4 H7 Plus vision module, I developed real-time image processing capabilities to enable dynamic target tracking and object manipulation.
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Key Technical Highlights:
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Vision Module Integration:
I leveraged the OpenMV4 H7 Plus, equipped with an OV5640 sensor, to capture and process images at QVGA resolution (320×240) at up to 25–50 FPS. Using MicroPython, I implemented color segmentation and thresholding algorithms—calibrated via the OpenMV threshold editor—to reliably track colored objects and faces.
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Communication & Data Processing:
The OpenMV module communicates with the Arduino control board over UART (using designated pins P4/P5), transmitting real-time data on target positions and features. I designed a custom protocol to ensure that these data packets are parsed correctly and used as inputs for the arm's control logic.
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Inverse Kinematics & Motion Control:
Once the vision module detects a target, I apply an inverse kinematics algorithm to convert the 2D image coordinates into precise 3D servo commands. These commands drive six PWM-controlled servos, achieving smooth, coordinated movement of the arm for tasks like sorting or grabbing.
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System Optimization:
To handle ambient lighting variations, I implemented dynamic threshold adjustments in the OpenMV code. Additionally, I fine-tuned the system’s error compensation for misalignment between the camera’s coordinate frame and the arm’s physical workspace, ensuring stable tracking even under challenging conditions.
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This integrated approach has allowed me to create a versatile, intelligent robotic arm capable of autonomously tracking and manipulating objects based on real-time visual feedback.
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The electronic and musical visual component was developed by Bowen, a co-doctoral student at the University of Glasgow.
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The engineer and art work was submitted to NIME2025 and Prix Ars Electronica.