A picking robot should fit your operation, not merely look efficient in a demonstration. In warehouse audits, I examine order software, inventory records, conveyor signals, and charging routines. The system should exchange accurate data with existing tools. Test real order peaks, not sample cartons. Small data delays can create large queues. Ask how exceptions are recorded, corrected, and reviewed. Integration is often less visible than speed. It still decides whether the project survives daily pressure.

Safety needs more than sensors and warning lights. Walk the actual aisles with operators, maintenance staff, and supervisors. Check stopping distances near shelves, people, doors, and temporary pallets. Review access controls, emergency procedures, inspection logs, and training records. A safe system must behave predictably after a network failure or misplaced item. Do not accept vague claims. Request witnessed tests and measurable limits. We sometimes underestimate quiet risks, especially during shift changes.

Operational compatibility is equally practical. Compare robot speed with picking rates, floor conditions, aisle widths, and replenishment patterns. Confirm who clears jams at 2 a.m. Also check spare parts, software updates, manual override, and technician response times. A system may perform well in a clean pilot area but struggle beside wet floors or overfilled locations. I have seen teams plan around ideal conditions. That was a mistake. Leave room for seasonal volume, human judgment, and imperfect inventory data. The best choice proves its value under ordinary pressure, not only during a polished trial.