Start Your Robotics Journey at SVRC
Whether you are an undergraduate exploring robotics for the first time, a graduate researcher collecting manipulation data, or a maker building your first robot arm, SVRC provides the hardware, learning paths, and community to get you from curiosity to capability.
Three paths from beginner to advanced
SVRC provides a structured progression from your first robot interaction to publishing research. Each level builds on the previous one, with clear milestones so you know when you are ready to advance.
Beginner: First Robot (Weeks 1-4)
Goal: operate a robot arm safely and understand how it works. What you learn: robot safety protocols, joint control basics, forward kinematics, and your first teleoperation session. Tools: OpenArm 101, Ubuntu, Python basics. Milestone: you can power on the arm, move it to a target position via teleoperation, and explain what each joint does. No prior robotics experience required — start with the Robotics Academy Layer A.
Intermediate: Data and Software (Weeks 5-12)
Goal: collect robot data and write control software. What you learn: ROS2 fundamentals (topics, services, actions), camera calibration, data recording with rosbag, HDF5 data formats, and basic imitation learning. Tools: ROS2 Humble, MoveIt2, OpenArm 101, Python. Milestone: you can collect 50 demonstrations of a pick-and-place task, store them in HDF5 format, and train a basic behavior cloning policy. Follow Academy Layers B and C.
Advanced: Research and Publication (Weeks 13+)
Goal: contribute to robotics research. What you learn: diffusion policies, VLA models (OpenVLA, Octo), sim-to-real transfer, data collection protocol design, experiment methodology, and paper writing. Tools: OpenArm 101 or DK1, SVRC Data Platform, LeRobot, MuJoCo/IsaacSim. Milestone: you can design and execute a complete experiment, train policies that generalize to new objects, and write a technical report suitable for a workshop submission.
Why OpenArm 101 is the right starter platform
Choosing your first robot is one of the most important decisions in your robotics journey. The wrong choice means weeks of frustration with setup, proprietary software, and dead-end skills. Here is why OpenArm 101 is the right starting point:
$4,500 — affordable for students and labs
A Franka Panda costs $20,000+. A UR3e costs $25,000+. OpenArm 101 gives you 6-DOF manipulation, 500g payload, and full ROS2 integration for $4,500. With student pricing, even personal purchase is within reach for graduate students with research funding. If buying is not in your budget, your university lab likely already has one or can get one through SVRC's academic program.
Open-source — learn the full stack
Hardware CAD, firmware source code, ROS2 drivers, and data collection tools are all open-source. You can read every line of code running on the robot. This is how you actually learn robotics — not by calling proprietary APIs with hidden implementations. Every skill you build on OpenArm transfers to any other ROS2-compatible platform.
Research-grade data collection
OpenArm 101 produces the same quality teleoperation data used in published research. It supports HDF5 and LeRobot data formats, synchronized camera feeds, and joint-level action recording. Your data is compatible with ACT, diffusion policy, and OpenVLA training pipelines. The data you collect on OpenArm can appear in a paper.
Community and documentation
Thousands of students, researchers, and makers use OpenArm. The Forum has indexed solutions for every common problem. The Developer Wiki covers every step from assembly to advanced data collection. When you get stuck, someone has already solved your problem and posted the answer.
Skills you will develop with SVRC
These are the specific technical skills that employers and research labs look for in robotics candidates. Each skill maps to a tool or project you can do with SVRC hardware and resources.
ROS2 and MoveIt2
The Robot Operating System 2 (ROS2) is the standard middleware in robotics research and industry. You will learn to write ROS2 nodes, work with topics and services, use tf2 for coordinate transforms, and plan motion with MoveIt2. These skills are required for virtually every robotics job posting.
Python robotics programming
Control robots with Python: joint-level commands, sensor reading, camera integration, and data processing. You will write scripts for data collection, calibration automation, and experiment execution. Python is the primary language for robot learning research.
Imitation learning and data collection
Learn how to design data collection protocols, operate teleoperation interfaces, record demonstrations in standard formats (HDF5, LeRobot), and train behavior cloning and diffusion policies. This is the core skill in modern robot learning research.
Sim-to-real transfer
Train policies in simulation (MuJoCo, IsaacSim) and deploy them on real hardware. Understand domain randomization, reward shaping, and the gap between simulated and real-world performance. Use the SVRC RL Environment and real hardware to validate transfer quality.
Free resources for students
Robotics Academy
Complete structured learning paths from hardware bringup through advanced robot learning. Free, public, and organized by skill level. Start here if you are new to robotics.
Open Academy →Developer Wiki and documentation
Full technical documentation for all SVRC hardware: assembly guides, firmware setup, ROS2 integration, SDK reference, and troubleshooting. Searchable and publicly accessible.
Open Wiki →Open datasets
SVRC publishes manipulation datasets in standard formats. Use them to train your first imitation learning policy without collecting your own data. Compatible with LeRobot and Open X-Embodiment pipelines.
Browse datasets →Model catalog and pretrained weights
Reference implementations and pretrained weights for common robot learning models: ACT, diffusion policy, OpenVLA, and Octo. Fine-tune on your own data or use as baselines for experiments.
Browse models →Portfolio projects you can build
A strong portfolio is what gets you interviews in robotics. Here are concrete projects you can complete with SVRC hardware, each designed to demonstrate a specific skill to employers or graduate admissions committees.
Teleoperation data collection pipeline
Skill demonstrated: data engineering, ROS2, systems integration. Build an end-to-end pipeline: teleoperate OpenArm 101, record synchronized camera + joint data in HDF5, validate data quality, and publish a small dataset. Document the protocol and share it on GitHub. Time: 2-3 weeks.
Imitation learning from demonstrations
Skill demonstrated: machine learning, experiment design, quantitative evaluation. Collect 100 demonstrations of a pick-and-place task, train a behavior cloning policy, evaluate success rate over 50 trials, and write a technical report with learning curves and failure analysis. Time: 4-6 weeks.
Custom end-effector design
Skill demonstrated: mechanical design, CAD, fabrication. Design a custom gripper for OpenArm 101 using the open-source CAD files as a starting point. 3D print it, test it on 3 different object types, and document grip force and success rates. Post the STL files and build log to the Forum. Time: 3-4 weeks.
Sim-to-real policy transfer
Skill demonstrated: simulation, RL, real-world deployment. Train a policy in MuJoCo using OpenArm URDF files, then deploy to real hardware and measure the performance gap. Document domain randomization settings, real vs sim success rates, and adaptation strategies. Time: 6-8 weeks. Advanced project.
Student discounts and opportunities
Student hardware pricing
Verified students receive discounted pricing on all SVRC hardware. OpenArm 101 student price is available on request. Email contact@roboticscenter.ai with your university email and student ID. Group orders for robotics clubs and course labs receive additional volume discounts. See the educator page for institutional pricing.
Internship and research positions
SVRC offers internship positions for students interested in robotics hardware, data collection operations, and platform engineering. Interns work directly with SVRC engineers at our Mountain View facility on real customer projects. Positions are available for undergraduates, graduate students, and gap-year builders. Email us with your resume and a link to any robotics project (GitHub, forum post, or video).
Lab visits and facility access
Students can visit the SVRC facility at 1117 Independence Ave, Mountain View, CA 94043 for hardware demos, lab tours, and supervised hardware sessions. East Coast students can visit 125 Western Ave, Allston, MA 02134. Schedule a visit by emailing contact@roboticscenter.ai at least 3 days in advance.
Showcase and recognition
Outstanding student projects are featured on the SVRC Showcase, shared with the community, and promoted to industry partners. If you build something notable with SVRC hardware, submit it for showcase consideration. We also provide letters of recommendation for students who contribute meaningfully to the SVRC open-source ecosystem.
What students say
"I built my first imitation learning pipeline on OpenArm 101 during my junior year. The documentation was good enough that I could work independently, and when I got stuck, the Forum had the answer within a day. That project became my capstone and got me into my top-choice PhD program."
— Undergraduate, Computer Science, UC Berkeley
"Our robotics club ordered 3 OpenArm units with the student discount. We went from unboxing to collecting teleoperation data in one weekend. By the end of the semester, two teams had trained working policies. We posted our build logs on the Forum and got feedback from SVRC engineers."
— Robotics Club President, Georgia Tech
"As a PhD student working on contact-rich manipulation, I needed real hardware data — simulation was not enough. SVRC let me collect 500 demonstrations at their Mountain View facility in a single week. The data was in HDF5 format and plugged directly into my training pipeline. That dataset was the core of my ICRA submission."
— PhD Candidate, Robotics, Stanford University
8 questions students ask most
1. Do I need my own robot to get started?
No. Start with the free Robotics Academy and Developer Wiki to learn concepts and software. Many exercises can be done in simulation. When you are ready for hardware, use your university lab's equipment, visit the SVRC facility, or apply for student pricing on your own unit.
2. What programming background do I need?
Basic Python proficiency is sufficient to start. You should be comfortable writing functions, using loops, and working with numpy arrays. No prior ROS2 experience is required — the Academy teaches it from scratch. If you can write a Python script that reads a CSV file and plots the data, you are ready.
3. How do I get student pricing?
Email contact@roboticscenter.ai from your university email address with your student ID and what you want to order. We verify your enrollment and respond with student pricing within 1 business day. The discount applies to all SVRC hardware.
4. Can I visit the SVRC lab?
Yes. Both our Mountain View (1117 Independence Ave) and Allston (125 Western Ave) facilities welcome student visitors. Email us at least 3 days in advance to schedule. Visits typically include a facility tour, hardware demos, and time with SVRC engineers to discuss your project or research interests.
5. How do I apply for an internship?
Send an email to contact@roboticscenter.ai with: (1) your resume, (2) a link to a robotics project you have worked on (GitHub repo, video, or forum post), and (3) a brief description of what you want to work on. We review applications on a rolling basis and respond within 2 weeks.
6. Can I use SVRC data and hardware for my thesis?
Yes. All SVRC open-source resources are free to use in academic work. SVRC datasets can be cited in publications. If you need to collect data at our facility for your thesis, contact us to discuss scheduling and access. We have hosted visiting researchers from multiple universities for data collection campaigns.
7. What should I build first?
Start with the teleoperation data collection project described above. It teaches ROS2, data formats, and systems integration in a concrete, completable project. You will have a working pipeline and a GitHub repo to show for it within 2-3 weeks. From there, move to the imitation learning project.
8. How does SVRC compare to just watching YouTube tutorials?
YouTube tutorials teach concepts. SVRC provides the structured path, real hardware, standard tools, and community feedback that turns concepts into skills. The difference between watching a video about imitation learning and actually collecting 100 demonstrations and training a policy is the difference between knowing about robotics and being able to do robotics.