Oscorp Autonomous Battery Sorting System

The Oscorp Autonomous Battery Sorting System is a retrofit, AI-driven robotic system that detects, classifies, and removes batteries from mixed waste and e-waste streams on a facility's existing conveyor lines. Deployed at battery recyclers and material recovery facilities (MRFs), it replaces dangerous manual sorting — reducing fire risk, lowering insurance premiums, and segregating lithium-ion chemistries to feed downstream black-mass and hydrometallurgical processes.

• Sensor fusion: computer vision (object class, brand, form factor, likely chemistry) + multi-energy X-ray (chemistry confirmation) + OCR (brand/text) — vision narrows priors, X-ray confirms, OCR reinforces.
• Sorting: robotic arms pick into up to 7 output streams, segregated by form factor and lithium-ion chemistry (NMC, LFP, LCO), with analytics on incoming waste composition.
• Training data: ~140,000 labelled battery and electronics objects to date, via an MOU with Livium, Australia's market-leading battery recycler.
• Throughput: continuous, fully autonomous operation at ~3 items/sec per arm, targeting 200+ items/min.
• Accuracy: ~90% with vision alone today (X-ray fusion in integration); roadmap target 99.5% by end of 2026, versus ~95% for manual sorters.
• Scope: current prototype handles payloads up to ~5 kg per pick and small-format / consumer batteries; larger EV modules/packs are out of scope for now.

As an early-stage startup, Oscorp Energy is at approximately TRL 6 (proof of concept deployed; prototype in assembly) and MRL 3–4 (prototype manufacturing underway). The platform is software-defined and modular: AI models update for new chemistries and labels without hardware changes, and capacity scales by adding pick arms and sensors as throughput needs grow.