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Danu Robotics

Danu Robotics manufactures AI-controlled robotic waste sorting systems designed for picking mixed recyclable materials in material recovery facilities. Their patented, retro-fittable two-arm robots integrate computer vision for high-accuracy object identification and efficient material separation. The company provides a cost-effective solution that minimizes disruption while improving operational performance in waste management.

Edinburgh, United KingdomFounded 202011500+ followers
Updated 20 months ago

Funding

$610K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

CC
Funding rounds are not available yet.

Founders

Product

Problem

Waste management facilities face challenges in efficiently sorting dry mixed recyclables due to reliance on manual sorting, leading to inefficiencies and difficulty in meeting increasing industry demands. Existing manual sorting operations struggle to maintain accuracy and throughput, hindering the transition to a circular economy.

Solution

Danu Robotics offers AI-controlled robotic systems designed to automate and enhance the sorting of dry mixed recyclables in waste management facilities. Their patented robotic systems utilize computer vision to identify target objects and high-efficiency grippers to accurately pick and drop materials. The AI "brain" continuously learns and improves its object recognition capabilities through the addition of new datasets and inputs from vision sensors. These robotic systems can be retrofitted into existing manual sorting operations with minimal disruption, increasing operational accuracy and throughput.

Target Audience

The primary target audience includes waste management facilities seeking to improve the efficiency, accuracy, and reliability of their dry mixed recyclables sorting operations.

Features

  • Patented series of robotic systems specifically designed for picking dry mixed recyclable materials.
  • Computer vision system outlines target objects, enabling high-efficiency grippers to successfully pick and drop materials.
  • AI-powered object recognition that improves with additional datasets and inputs from new vision sensors.
  • Retrofittable design allows for easy installation into existing manual waste sorting facilities with minimal disruption.
  • Base-level two-arm system requires less than 1 meter of conveyor space.
  • High wear components like grippers can be exchanged in approximately 20 minutes.
  • 90% of the robotic systems are recyclable.
This profile is AI-generated and may contain inaccuracies.