Available Now
Book a demo and get early access. Free trial!
What’s a Queueing System (in Isaac terms)?
June 7, 2025
When you're setting up a simulation in Isaac Sim—say you're modeling robots in a warehouse, cars at a checkpoint, or planes at a gate—you're essentially building a queueing system. Every time an agent waits to get into a workspace, a charger, or a station, you’re dealing with queues.
It’s any scenario where multiple agents (robots, vehicles, etc.) arrive over time and need access to a limited number of resources (like docks, tools, or processors). The system has three parts:
1. Arrival Process
This describes how often agents show up. In simulation terms, this could be your robot's task frequency, delivery vehicle scheduling, or customer arrival at a kiosk.
Isaac lets you script this using Python or behavior trees—so you control whether arrivals are random (stochastic) or fixed (deterministic).
- If arrivals are random, we usually describe them using distributions (like exponential or Gaussian).
- Example: You simulate 10 robots arriving every 30 seconds—but some might show up sooner or later depending on the randomness.
2. Service Mechanism
This is what the agents are waiting for—charging ports, conveyor access, machine arms, CPU cycles, etc.
You define how many "servers" you have in your simulation. Each server could be a robot arm, a docking station, or a workstation.
In Isaac, you'd model this by instancing components and assigning them logic for how long they "work" on each agent (this is the service time).
3. Queue Discipline
This is how you decide who gets served next. Isaac doesn’t enforce this by default—you script it.
- FIFO (First-In, First-Out): The first robot that arrives gets access first. Most natural for physical systems.
- LIFO (Last-In, First-Out): Newest job gets handled first. Rare in robotics, but may show up in buffer logic.
- Priority: Higher-priority agents (maybe emergency vehicles or low-battery bots) go first. You’ll often script this manually using custom sort logic.
🧠 The Common Setup: GI/G/s
When you see a system called GI/G/s, here’s how to read it in Isaac terms:
- GI: You define your own logic for how agents arrive. Could be random, could be scripted.
- G: You define how long it takes for a resource to serve an agent—again, random or fixed.
- s: Number of service stations (charging points, loading bays, etc.)
🔄 Why it matters for simulation performance
In Isaac Sim, if you want realistic throughput, congestion, and latency modeling, you need to tune these queue settings. You’re not just animating objects—you’re modeling real-world bottlenecks.
Also: If you’re training AI (e.g., reinforcement learning), queueing effects impact your agent’s learning loop. A robot that always waits 15 seconds before action will behave very differently from one that gets immediate access.
🔧 Tip: Use omni.isaac.core.utils and Python callbacks
To implement queues practically in Isaac Sim:
- Track agents entering and leaving a queue using collision or trigger events.
- Assign service times via timers or task graphs.
- Use lists or priority queues in Python to manage order.
- You can simulate
GI/G/sdynamics even without formal libraries—just by scripting.
💡 Ready to eliminate guesswork from your simulations?
Champion helps engineers build reliable, repeatable, and automated simulation pipelines—so you can focus on results, not rework. From CAD to physics to AI-driven validation, Champion turns simulations from a one-off experiment into real infrastructure.
👉 Build smarter. Simulate faster. Trust the output.
Explore Champion →