AI Labs where students build and train real AI — from machine learning to humanoid robotics

An AI lab is a dedicated space where students and researchers work hands-on with physical robots to learn artificial intelligence, machine learning, computer vision, and autonomous control. Instead of only running code in a simulator, learners program robots like the NAO research humanoid, Unitree Go2 quadruped, or AgileX mobile platforms to perceive, decide, and act in the real world. The goal is to connect abstract AI concepts to tangible behavior – perception, path planning, human-robot interaction, and reinforcement learning.

Cost depends heavily on the platforms and lab size you choose, so ranges vary widely – a single research humanoid or quadruped is a different budget than a multi-station lab serving a full cohort. Entry research platforms typically start in the low-to-mid four figures, while advanced humanoids and autonomous ground vehicles run higher. For an accurate, itemized figure for your specific platforms and seat count, request a quote on this page and we’ll build it around your goals.

Common platforms include the NAO and SoftBank Pepper humanoids for human-robot interaction and social AI, the Unitree Go2 quadruped for locomotion and perception research, and AgileX Tracer mobile bases for autonomous navigation and SLAM. Specialized platforms like the Blueye underwater drone extend research into marine environments, and Firia tools support younger coders learning the fundamentals. We carry 147 products across this capability so the lab can be matched to your research focus and student level.

Both. Platforms like the NAO Research edition, AgileX Tracer – Research, and the Unitree Go2 Professional Grade are built for serious work and are used in university labs for AI, robotics, and HRI research. The AgileX Tracer AGV, for example, is trusted by programs like Georgia Tech. The same platforms also support undergraduate coursework and capstone projects, so one lab can serve teaching and research.

Students typically work in Python and C++, and many platforms support ROS (Robot Operating System), the standard framework for modern robotics research. They build practical skills in computer vision, machine learning, sensor fusion, motion planning, and autonomous decision-making. For younger learners, block-based and beginner-friendly tools (such as Firia’s offerings) provide an on-ramp before they move into text-based coding.

Yes – AI and robotics labs are frequent targets for STEM, CTE (Career and Technical Education), and research-equipment grants, and many institutions fund them through capital or technology budgets. Programs like NSF awards, state STEM initiatives, and workforce-development funds commonly cover this kind of equipment. We can provide quotes, spec sheets, and capability descriptions to support your grant application; ask us what documentation you need.

A well-designed lab maps to computer science and engineering standards by giving students measurable outcomes in coding, AI/ML concepts, and applied problem-solving. Working with physical robots reinforces the full cycle of design, programming, testing, and iteration that standards emphasize. Because platforms span beginner to research grade, you can scaffold outcomes from introductory coding through advanced autonomous-systems work.

It doesn’t have to be. RobotLAB provides training on the platforms so instructors can teach confidently even without a deep robotics background, and many of these robots ship with documentation, SDKs, and example projects to shorten the ramp-up. We also offer ongoing maintenance and support so faculty can focus on teaching rather than troubleshooting hardware. Ask us about training options when you request your quote.

Most platforms need standard classroom or lab space, reliable Wi-Fi, and computers capable of running development tools and ROS; mobile robots like the AgileX Tracer and Unitree Go2 also need clear floor area to move and be tested safely. Humanoids such as NAO and Pepper are tabletop-to-floor scale and store in transport and storage cases between sessions. We can help you plan layout, power, and networking based on the exact platforms you choose.

Yes, and most programs do. You can begin with a single platform or a few stations to prove out the program, then add robots and capability tiers as enrollment, grant funding, or research scope grows. Because the platforms share common tools like Python and ROS, the skills and curriculum you build early carry forward as you scale.

RobotLAB offers maintenance services and nationwide service support to keep lab robots operational across the school year or research cycle. Routine maintenance, repairs, and replacement parts are handled so downtime stays minimal. Transport and storage cases for platforms like NAO and Pepper also help protect the equipment between uses and during transit.

Tell us your student level, research focus, and budget, and we’ll recommend the right platforms and build an itemized quote – including documentation to support grant applications. We can also arrange a demo so you can see the robots in action before committing. To get started, use the form on this page or call 1-87-RobotLAB.