Skills useful to learn for robotics engineering

Robotics is a very hot industry, and today, the hottest place within it is humanoid robotics. We previously published two deepdives on this topic with Sandor Felber, who’s been a Robot Learning Researcher at MIT, and a Robotics R&D Engineer at Tesla in California, among other roles. The articles cover relevant topics at the intersection of AI, robotics, and software engineering. Since the last deepdive, Sandor has cofounded Nyro Humanoids, an early-stage startup headquartered in San Francisco that aims to build and deploy humanoid robots in the real world.

In the third and final deepdive in this series, we take a close look at skills useful for joining this field, covering:

1. Software engineering skills

2. AI skills

3. Robotics fundamentals

4. Advice for studying a Master’s in Robotics

5. Influential perspectives

6. Why get into robotics?

Previous issues cover:

Robotics basics for software engineers (part 1):

• Getting into robotics

• Robotics industry overview

• Planning a robotics project

• Development phase

• Tech stack and tools (and how Python, C, C++, and Rust are popular)

• Testing, demoing, and shipping

• Day-to-day as a robot builder

Robotics for software engineers: humanoid robots (part 2):

• Why the humanoid form?

• Hardware challenges

• Software engineering challenges

• Show me the code! Real-time robotics optimization

• Real-world optimization techniques

• How AI is changing robotic optimization

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With this, it’s over to Sandor:

We're standing on the threshold of a robotics revolution. Just as OpenAI's ChatGPT “moment” transformed how we think about artificial intelligence (AI), the robotics industry is approaching its own breakthrough. This looks less like a step-like change, and more of a gradual transformation – one that will fundamentally change how we approach physical AI.

At Nyro Humanoids, we're creating the intelligence that powers humanoid systems capable of operating where humans cannot – or should not – go. From disaster response missions to save lives, to potentially dangerous construction sites, and toxic industrial environments that require hazardous activities which can put health at risk, our autonomous humanoid robots represent the cutting edge of what we call ‘physical AI’.

Our mission is to deploy intelligent humanoid robots in high-risk environments to protect human life and expand the boundaries of what's possible. Whether it's navigating collapsed buildings during search and rescue operations, handling hazardous materials, or operating in challenging conditions, we are developing the cognitive capabilities that enable robots to think, adapt, and act autonomously when every second counts.

The same breakthroughs that have revolutionized language models are now being applied to physically embodied intelligence. There are computers with arms and legs – robots! – which can understand their environment, make complex decisions, and execute precise physical actions in real time.

What follows is a comprehensive guide to the skills, technologies, and mindset that I’ve developed on my journey. Whether you're a software engineer looking to make the leap into robotics, a student considering the next move, or you’re simply curious about this rapidly-evolving field, this deepdive is a roadmap for becoming part of the robotics revolution.

The future isn't just about smarter software, it's about intelligence that can move, manipulate, and operate in the physical world. At Nyro Humanoids, we are building it one training run at a time – and we’re also hiring.

Building robots is a multidisciplinary endeavour that blends pragmatic software engineering, AI expertise, and a deep understanding of robotics fundamentals. What follows is a breakdown of the key skills that have proven invaluable to me every day in engineering robotics software and hardware.

1. Software engineering skills

Software, electrical, and mechanical engineering are the backbone of robotics. Let’s consider software engineering, where skills that prioritize performance, scalability, and reliability, are critical catalysts required to build robots that succeed in real-world applications. Depending on the kind of robotics you get into, some areas of interest might be:

Communication protocols, such as:

• CAN Bus (Controller Area Network Bus)

• The TCP/IP networking stack and peer-to-peer, or multiple node connections including graph theory. Both are important for designing robust communication systems between single and multi-robot systems, and their hardware and software components.

• ROS2 middleware: Robot Operating System 2: a middleware acting as a meta-operating system for a robot and its controller, or a remote controller.

• Performance optimization. Coding algorithms are efficient in power consumption by minimizing CPU, GPU and/or memory usage. One example of the necessity of performance optimization is batteries. With overly resource-intensive software, the CPU could require thermal throttling or else overheat. If your code isn’t efficient and the CPU draws lots of power, then the robot’s battery won’t last as long, and might require additional cooling heat sinks to be installed. Basically, high-performance and efficient code are must haves, not nice-to-haves, for real-world robotics.

Multithreading and multiprocessing: managing parallel processes in C/C++, Python, or Rust, for r