Autonomous Warehouse Operations — LogiNext Robotics
Visual: robot fleet, picking lanes, and orchestration board.
Client Overview
LogiNext Robotics provides integrated autonomous solutions for high-throughput warehouses. This project focused on automating putaway, picking with vision-guided arms, and fleet orchestration to improve throughput and reduce labor dependency at a distribution center serving e-commerce clients.
Challenge
Manual picking and putaway were labour-intensive and error-prone during peaks. The facility wanted a safe autonomous fleet that worked alongside humans, reduced picking errors, and scaled throughput without proportionate headcount increases.
Solution — Robot Fleet & Vision Picking
We deployed an integrated system of autonomous mobile robots (AMRs) for transport, vision-guided pick arms for small items, and a central orchestration engine that schedules tasks, manages collision avoidance and optimizes throughput under SLA constraints.
Core capabilities
Approach
- Prototype pick + transport loop in a controlled zone and measure cycle times vs manual.
- Iterate on vision models for SKU variance and lighting conditions.
- Scale AMR coverage and integrate orchestration with WMS picking waves.
- Safety acceptance testing and operator retraining for human-robot collaboration.
Technology stack
Implementation — Delivery Phases
Phase 1 — Prototype (Weeks 1–10)
Validate pick arm performance for representative SKUs and pilot AMR navigation in aisles.
Phase 2 — Orchestration & Scale (Weeks 11–26)
Build orchestration engine to batch tasks and optimize congestion-aware routing for AMRs.
Phase 3 — Safety & Human Ops (Weeks 27–38)
Implement human detection, safety zones, and operator training for co-working with robots.
Phase 4 — Full Deployment (Weeks 39–44)
Scale across the picking footprint and tune for peak-day throughput.
Impact & Results
40%
Increase in picking throughput (pilot zones)
60%
Reduction in labor required per pick
50%
Lower picking error rate
Months
Time to full throughput improvements
Qualitative outcomes
- Robots handled repetitive work, freeing staff for exception handling and quality control.
- Orchestration reduced congestion and improved cycle predictability during peaks.
- Human-robot collaboration required careful change management but yielded long-term gains.
Client Testimonial
Key Highlights & Learnings
- Prototype small zones first to prove vision models and navigation reliability.
- Operator training and safety acceptance are critical for rapid adoption.
- Orchestration yields compounding benefits—optimize flows, not just robots.