Building centralized AMR brain system for next generation smart port - ON-1189

Project type: Research
Desired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences, Operations research
Company: AiNOS AI
Project Length: 6 months to 1 year
Preferred start date: 09/01/2026
Language requirement: English
Location(s): Toronto, ON, Canada
No. of positions: 3
Desired education level: PhDPostdoctoral fellow
Open to applicants registered at an institution outside of Canada: No

About the company: 

AiNOS AI is an applied artificial intelligence company building next-generation AI technology for smart ports and other complex industrial environments where autonomous systems, infrastructure, and operations must work together in real time.

The company develops AI-native software and operational intelligence platforms that help orchestrate autonomous machines, logistics flows, and decision-making across dynamic environments such as ports, shipyards, and advanced manufacturing systems.

Its focus is on enabling more intelligent, resilient, and scalable operations through system-level modeling, optimization, simulation, and digital twin capabilities. In the Smart Port context, this includes supporting coordination across autonomous ground vehicles, cargo movement, routing, scheduling, yard operations, and broader logistics infrastructure.

AiNOS works with international partners to advance the technology foundation required for more autonomous, efficient, and adaptive industrial operations.

Describe the project.: 

This research develops a centralized intelligence layer — a Centralized AMR Brain — to model and orchestrate autonomous port operations as a unified system.
Modern ports involve tightly coupled components, including autonomous mobile robots (AMRs), cranes, cargo flows, storage areas, traffic lanes, and operational constraints. Existing approaches often optimize these components in isolation, leading to bottlenecks and suboptimal system-wide performance.
To address this limitation, the project investigates a system-of-systems framework that enables holistic coordination and decision-making across all port activities. The Centralized AMR Brain integrates system-level representations of assets, workflows, and constraints to support:
• Multi-agent coordination across robots and infrastructure
• Dynamic routing, scheduling, and task allocation
• Constraint-aware optimization under uncertainty
• Simulation and digital twin environments for evaluation
• Robustness under disruptions such as congestion, delays, and equipment downtime
The research also explores simulation environments to evaluate operational strategies under realistic scenarios, measuring throughput, utilization, and resilience.
By unifying perception, planning, and control into a single intelligence layer, this work establishes a foundation for next-generation Smart Port AI infrastructure. The Centralized AMR Brain enables globally optimized operations and provides a scalable platform for future extensions, including ontology-driven representations, adaptive control systems, and broader autonomous coordination.

Required expertise/skills: 

Desired expertise includes:

• Operations research, optimization, or industrial engineering
• Systems modeling, simulation, or digital twin development
• Robotics, autonomous systems, or multi-agent coordination
• Python-based data science and engineering workflows
• Mathematical modeling, statistics, or applied machine learning
• Scheduling, routing, or resource allocation algorithms
• Experience working with logistics, transportation, or infrastructure systems (asset)

Additional strengths may include experience with simulation frameworks, graph-based system representations, or experimentation in complex operational environments.