Rose City Robotics develops autonomous robotic systems for the disassembly and direct recycling of lithium-ion electric vehicle batteries, utilizing machine learning and transformer neural networks for adaptive motion planning. The technology aims to increase battery material recovery rates from 5% to over 90%, reducing waste and emissions in the recycling process.
Funding
Funding not disclosed
Founders
Product
Problem
The current methods for recycling lithium-ion electric vehicle (EV) batteries are inefficient, recovering only a small fraction of valuable materials. This leads to significant waste and environmental impact, hindering the development of a truly circular economy for battery materials. Traditional recycling processes often involve manual disassembly, which is dangerous and not scalable.
Solution
Rose City Robotics develops autonomous robotic systems that automate the disassembly and recycling of lithium-ion EV batteries. By leveraging machine learning and transformer neural networks, their technology enables adaptive motion planning for robots, allowing them to handle the complex and variable task of battery disassembly. This approach significantly increases material recovery rates, reduces waste, and minimizes the environmental impact associated with battery recycling. The company's solutions aim to create a safe, effective, and scalable process for recovering critical materials from end-of-life batteries, ensuring these resources are available for future clean energy and electrification solutions.
Target Audience
The primary customers are battery recycling facilities, electric vehicle manufacturers, and other organizations involved in the end-of-life management of lithium-ion batteries.
Features
- Autonomous robotic disassembly of lithium-ion EV batteries
- Machine learning and transformer neural networks for adaptive motion planning
- Utilizes sensor and vision data to enhance robot hardware
- Increases battery material recovery rates from 5% to over 90%
- Custom software development for enhanced control and interfaces
- Digital twin modeling for visualization and planning
- Hardware agnostic specifications, partnering with leading robotics vendors like FANUC, ABB, Universal Robots, and Kuka