WorkspaceWizardPCB

Workspace Wizard

Team Members:

• Ishaan Salian
• Aryaman Ghura
• Kavya Manchanda
• Mary Esenther

Project Overview
Workspace Wizard is an autonomous desk organization system designed to optimize workspace management by identifying, sorting, and organizing objects on a desk. The system uses a combination of hardware and software to detect object positions, plan efficient placement paths, and execute movements to organize objects with high precision.

Key Features:

• Object Detection & Recognition: The system uses a camera and machine learning models to identify and track objects on the desk.
• Pathfinding Algorithm: The robot calculates optimal paths for organizing objects, avoiding obstacles and ensuring an efficient layout.
• Autonomous Movement: The robot uses motors and tracks to move objects into predefined positions while respecting boundaries and object types.
• Task Automation: The robot performs "knolling" (arranging objects neatly and systematically) by aligning objects with a target orientation and spacing.

Technologies Used:

• Hardware:
  • Nvidia Jetson (for processing and computation)
  • Servo motors and tracks (for movement)
  • Custom PCB (for controls)
  • USB Camera (for object detection and tracking)
  • Power management system (for optimal battery usage)
• Software:
  • Python (for control logic and algorithms)
  • OpenCV (for computer vision tasks)

References:

• Hu, Y., Zhang, Z., Zhu, X., Liu, R., Philippe Martin Wyder, & Lipson, H. (2023). Knolling bot: Learning robotic object arrangement from tidy demonstrations. https://api.semanticscholar.org/CorpusID:268513198