Leader
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Hosting Facilities
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CoBolt
Automation
Collaborative Battery recycling: Optimization of Light operations pre-Teardown
Challenge: Semi-automated EV battery disassembly for recycling
CoBolt is a pilot project addressing semi-automated EV battery disassembly for recycling. It utilizes an AI-driven, data-enabled collaborative mobile robot, TIAGo Pro, to automate the demanding task of unscrewing and removing the external lids of EV batteries. By equipping the robot with AI perception, custom tooling, and human-aware navigation, the solution identifies various battery models and autonomously performs the unscrewing. This innovation improves operational efficiency and recycling throughput, reduces worker fatigue and injury risks, and offers a highly flexible, modular alternative to static production lines
Leader
Hosting Facilities
PAL Robotics operates state-of-the-art production facilities located at its headquarters in Barcelona. These facilities are equipped with cutting-edge technology that enables the in-house design, manufacturing, assembly, and integration of advanced robotic components and service robots. This infrastructure allows for the rigorous validation of complex systems in controlled environments, ensuring high reliability and robustness.
Background
The first crucial step in EV battery recycling involves the removal of the external lid, which is fastened by screws along the battery’s entire periphery. Currently, this demanufacturing process is performed manually in semi-structured, ergonomically challenging environments, causing significant worker fatigue, injury risks, and operational inefficiencies. While standard automation with static robotic arms could perform this, it requires heavy investments and shop floor reconfigurations unsuitable for smaller recycling operations. A flexible, cost-effective automation solution is required to improve safety and throughput.
Solution
CoBolt deploys TIAGo Pro, a highly modular autonomous mobile manipulator developed by PAL Robotics. The robot features 7-degrees-of-freedom arms, a lifting torso, and will be equipped with custom demanufacturing tools specifically integrated for unscrewing operations. The system uses AI-based perception via RGB-D cameras to recognize varied battery models, calculating precise poses for screw locations. Combining human-aware navigation, visual servoing, and torque-controlled mechanical action, the robot autonomously moves around the battery to execute the disassembly. This mobile approach bypasses the need for large, static assembly lines, making it ideal for smaller recycling businesses. The integrated ROS2 software pipeline unifies perception, manipulation, and navigation to remove humans from the strenuous unscrewing tasks while maintaining safety and high spatial accuracy.
Objectives
- Deliver a mobile collaborative robotic solution equipped with AI perception and custom unscrewing tools for EV battery dismantling.
- Achieve a robot assistance rate >50% to reduce the physical workload of operators and improve ergonomic conditions by >15%.
- Increase battery recycling throughput by >5% to recover Critical Raw Materials, directly supporting the European Green Deal.
- Ensure robustness across varied battery models by achieving an aggregated AI object detection accuracy of >75%.
- Attain an overall robotic efficiency success rate of >80% for the aggregated dismantling operations.
KPIs achieved
Development
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Feedback
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Mauris et nulla tellus. Nulla consectetur placerat nunc placerat bibendum. Sed sit amet consequat ex. Pellentesque id odio felis. Etiam tellus dui, maximus non vehicula ut, suscipit vel ex. Maecenas quis lorem ut sem aliquet fermentum.
Mauris et nulla tellus. Nulla consectetur placerat nunc placerat bibendum. Sed sit amet consequat ex. Pellentesque id odio felis. Etiam tellus dui, maximus non vehicula ut, suscipit vel ex. Maecenas quis lorem ut sem aliquet fermentum.