When most people start freelancing in robotics, they begin alone. Small projects come first, then bigger ones. Over time, skills improve, communication gets better, and confidence grows. But there is one problem many freelancers face: how do you measure real progress?
Writing more code does not always mean you are moving forward. Building more demos does not mean you are closer to production. This is where Technology Readiness Level (TRL) becomes useful.
Originally defined by NASA, Technology Readiness Level is a simple framework that helps engineers understand how close a technology is to real-world use. In robotics software development, TRL is one of the clearest ways to track growth, choose better projects, and move from experiments to production-ready systems.
This article explains TRL in practical terms, with a focus on robotics simulation, real robots, and market readiness.
What Is Technology Readiness Level?
Technology Readiness Level (TRL) is a nine-level scale used to measure the maturity of a technology.
- TRL 1 is an idea or basic research
- TRL 9 is a fully deployed, production-ready system
NASA introduced TRL to reduce risk in complex systems and avoid deploying untested technology into critical missions. Today, the same framework is widely used in robotics, aerospace, defence, and deep tech industries.
You can read the original NASA definition here:
https://www.nasa.gov/directorates/heo/scan/engineering/technology/technology_readiness_level/
Why TRL Matters in Robotics Software Development
Robotics is not like web or mobile development. Software does not live in isolation. It interacts with motors, sensors, power systems, environments, and people.
Many robotics projects fail not because the code is bad, but because the technology is not ready.
TRL helps answer questions such as:
- Is this idea only theoretical?
- Has it been tested in simulation?
- Has it worked on a real robot?
- Is it stable enough for production?
For freelancers, TRL also helps in project selection. Working only on low-TRL projects for years can slow long-term growth.
Understanding TRL Levels in Robotics
TRL 1–2: Ideas and Early Research
At this stage, the focus is on concepts.
Examples:
- ESP32-based demo robots
- Small IoT robotics experiments
- Proof-of-concept AI models with no deployment plan
These projects are useful for learning, but they are not meant for production. Most will never reach the market.
TRL 3–4: Robotics Simulation Becomes Essential
This is where robotics simulation becomes critical.
At TRL 3 and 4:
- The idea is tested in software
- Behaviour is validated in a simulated environment
- Failures are cheap and safe
Simulation helps answer one key question:
Does this idea work at all?
If it does not work in simulation, it should not be tested on a real robot.
Popular simulation platforms include Gazebo, Isaac Sim, and Webots. Simulation allows repeatable tests, faster iteration, and early detection of design flaws.
TRL 5–6: Real Robot Integration
This is where many projects struggle.
At these levels:
- Software is deployed on a real robot
- Sensors, actuators, and control loops are tested together
- The environment starts to matter
Unlike simulation, hardware testing is slower and riskier. You cannot run hundreds of tests in parallel. Each test costs time and money.
This is where testing discipline becomes important.
TRL 7–8: Pre-Production Systems
Here, the system is close to real use.
Characteristics:
- Stable hardware
- Controlled real-world environments
- Defined operating limits
- Repeatable behaviour
As a freelancer, reaching TRL 7 or 8 usually means working with clients who:
- Already own robots
- Understand robotics constraints
- Are preparing for real deployment
TRL 9: Production and Market Readiness
TRL 9 is rare in robotics.
It means:
- The robot is deployed
- Customers are using it
- Failures have real consequences
Very few robotics companies reach this level successfully. Those that do have strong testing, clear use cases, and realistic expectations.
This is where robotics market readiness truly matters.
Simulation vs Real Robots: A Simple Rule
A useful rule shared by experienced engineers is:
- If it does not work in simulation, do not try it on hardware
- If it works in simulation but fails on hardware, the gap is physical
Simulation reduces risk. Real robots confirm reality.
This is why tools like NVIDIA Isaac Sim have become popular in modern robotics pipelines:
https://developer.nvidia.com/isaac-sim
Choosing Better Freelance Robotics Projects Using TRL
Consider two projects:
- A high-budget humanoid simulation project with no robot
- A slightly lower-budget project with a real robot and deployment plan
From a TRL perspective, the second project is more valuable.
Working on real systems teaches:
- Hardware-software integration
- Testing strategies
- Environmental constraints
- Production thinking
These skills cannot be learned from theory alone.
Why Testing Matters More Than Code
In early projects, most people focus only on “making it work”.
At higher TRL levels:
- Tests reduce risk
- Failures are expected
- Stability matters more than novelty
In simulation, you might run 100 automated tests.
On hardware, you may run only 20–30 carefully selected tests.
Both are necessary.
Simple Example: Readiness Check in Code
Below is a very simple example showing how a readiness check might be structured before deploying to hardware.
def readiness_check(simulation_passed, hardware_available, tests_completed):
if not simulation_passed:
return “Stop: Fix simulation first”
if not hardware_available:
return “Wait: No robot available”
if tests_completed < 20:
return “Not ready: Increase hardware tests”
return “Ready for next TRL stage”
This logic reflects real TRL thinking: progress only when prerequisites are met.
Visualising TRL Progress (Chart Explanation)
Imagine a simple chart:
- X-axis: TRL level (1 to 9)
- Y-axis: Risk level
The chart slopes downward.
- High risk at TRL 1–2
- Medium risk during simulation (TRL 3–4)
- Controlled risk during real robot testing (TRL 5–7)
- Lower operational risk at TRL 8–9
The goal is not to eliminate risk, but to reduce it step by step.
Physical AI and the Future of TRL
The industry is moving towards physical AI: intelligence that leaves the screen and interacts with the real world.
Humanoid robots, mobile manipulators, and autonomous systems require:
- Generalisation
- Robust perception
- Reliable control
This increases the importance of TRL. Ambitious ideas without readiness will fail faster in the real world.
Key Takeaway for Robotics Freelancers
If you want to grow:
- Do not stay forever at TRL 1–3
- Use robotics simulation properly
- Target clients with real robots
- Think about market readiness, not just demos
Technology Readiness Level gives you a clear, honest way to measure progress.
Frequently Asked Questions
1. What is Technology Readiness Level in simple terms?
It is a scale from 1 to 9 that shows how close a technology is to real-world use.
2. Why is TRL important in robotics?
Because robotics involves hardware, software, and environments, and failures are costly.
3. At what TRL should simulation be used?
Simulation is critical at TRL 3 and 4, before testing on real robots.
4. Can freelancers work on high TRL projects?
Yes, especially at TRL 5–8, if clients already have robots and deployment plans.
5. Does every robotics project reach TRL 9?
No. Many projects stop at research or prototype stages and never reach production.
Technology Readiness Level is more than a framework; it is a practical way for robotics freelancers to measure real progress, reduce risk, and move beyond demos toward production-ready systems. By thinking in TRL stages, engineers shift their focus from writing more code to building validated, testable, and deployable solutions using simulation, structured hardware testing, and realistic constraints. As robotics moves toward physical AI and real-world deployment, this mindset becomes essential. To support this progression, structured learning paths such as our robotics learning paths that guide engineers from fundamentals to simulation and real-robot integration help ensure growth is intentional, aligned with TRL stages, and focused on real market readiness.