Best Laptops for Robotics Engineering or ROS Development

Best Laptops for ROS or Robotics Engineering

If you are looking for the best laptop for robotics, you have come to the right website. Even though robotics may not be as mainstream as computer science or data science, it is undoubtedly one of the most exciting engineering fields out there. Many people enter robotics through computer science. Robotics engineering is an interdisciplinary area of mechanics, electronics, and computer science. Developing robotics software requires knowledge of data structure and algorithms. ROS or Robotic Operation System is a collection of software for robot software development. There are many types of robotics. A good laptop or computer can help us become a better robotics developers. Without further ado, let's dive into lists of the best laptops for robotics programming or engineering.

CPU & GPU

ROS programming doesn't require GPU-heavy computing power. We recommend a CPU with a high single-core frequency. However, most of the ROS tasks are CPU intensive. On the other hand, some robotics programming tasks heavily rely on machine learning and AI. In that case, we recommend going with NVIDIA graphics because of parallel computing software called CUDA.

So if you are looking for a laptop that serves both ROS and machine learning, we would recommend laptops with great CPU and GPU specifications. However, starting in the ROS or Robotics field, you should primarily focus on CPU-heavy laptops. 

Operating System:

Debian-based operating systems such as Ubuntu are the best OS because robotics programs release in Linux first. Support for Windows is pretty great, too, since Windows still dominates the market share in the operating system arena. Although Windows now support WSL2, it isn't full features of Linux, so it might not always get the job done. In that case, dual boot still is a great option. Some people may think that macOS doesn't have similar compatibility as Linux OS like Ubuntu. However, it is no longer valid because if you look at several ROS clients like Gazebo client, they allow installing and running on macOS. 

For more information on Gazebo, client installation guide, check out their installation page: Gazebo Installation. 

ROS2 Iron Installation guide ROS Installation Page​

Even if you have an M1 mac, you can still run it via Rosetta. To run programs meant for intel-based computers, you can select open with Rosetta by right-clicking on the application and selecting get info, and there should be an "open using the Rosetta" box. Arm-based CPUs are great since they outperform almost all other CPU architectures. So if you plan to run mostly ROS software and programs, then the M1 mac will serve the purpose much better than Intel or AMD. However, the M1 mac falls short in the GPU department. So naturally, when it comes to GPU-based programs like machine learning and AI, the M1 mac will be way behind dedicated graphics because it doesn't support external GPU yet. It would be best to stick to Intel-based or X86 architecture for better graphics support from NVIDIA or AMD. 

Another factor is the programming language for ROS. Both Python and C++ are used heavily in this field. However, most people prefer Python over C++ whenever it is possible to do so. Although Python is way slower than C++, Python is mainly used on the front-end or client-side of robotics programming.

RAM & SSD:

ROS doesn't require a lot of RAM. 16GB RAM should be good enough for most ROS tasks unless you run extensive area simulations and large maps. However, saving large bag files of sensor data take up a lot of space, so we recommend getting at least 512GB SSD. If adding SSD costs more than the external SSD on the market, the thunderbolt three interfaces should come to the rescue, allowing up to 40Gbps transfer rate.