AI Brain + Robotic Body
Embodied AI pairs foundation models with physical robotics, enabling agents to perceive, reason, and act in the physical world.
Why Embodied AI & Data Collection Matter
General Manipulation
Connect with a team working on practical and capable robotic systems.
Fueling Imitation Learning
Embodied models learn by mimicking human demonstrations. High-quality real trajectory data is essential for training robust policies.
Overcoming Sim-to-Real Gap
Simulators fail to capture real physics and friction. Real teleoperation data on physical hardware ensures seamless deployment.
Data Collection Hardware Solutions We Can Provide
Enable real-time teleoperation with a 1:1 master–follower setup using myArm M750 and C650.
Enables capturing synchronized robot state data, end-effector motion trajectories, and RGB visual streams.
Generates high-quality human demonstration data for imitation learning and VLA model training.
Seamlessly compatible with open-source ecosystems like ROS/ROS2, ALOHA, and LeRobot.
Lightweight, out-of-the-box desktop solution built for robotics labs and developers.
Join the Embodied AI Research Program
We support global research teams with dedicated hardware funding, co-marketing exposure, and direct engineering support to advance real-world Embodied AI applications—submit your proposal below to unlock research collaboration opportunities.
What You Get
Featured research hardware, technical support, and open-source resources — 50% off
50% off Professional Hardware
Save up to $1,429 on myArm M&C series and myGripper H100 dexterous hands.
ROS & ROS2 Ecosystem
Includes full ROS/ ROS2 driver packages and MoveIt configs for rapid simulation and control.
Open-Source Code & SDKs
Access Python/ C++ SDKs, low-level APIs, and demo code on our official GitHub repository.
Dedicated Technical Support
Enjoy direct technical support for setup, control APIs, hardware integration, and troubleshooting.
Who Should Apply
This project sponsorship program supports Europe and the UK only.
Embodied AI & Robotics Labs
Open to lab leaders, faculty, and research teams focusing on Embodied AI, foundation models, and robotics.
Data Collection & Learning Teams
Open to researchers and students advancing teleoperation data collection, imitation learning, and VLA models.
Dexterous Manipulation Researchers
Open to researchers and engineers developing bi-manual control, dexterous hands, and tactile sensing algorithms.
Open Source Community Contributors
Open to enterprise R&D leads and influential contributors in the open-source robotics community.
What We Expect
Paper and Code Citations
Cite Elephant Robotics and the hardware model in published papers (main text/appendix) or GitHub READMEs.
Results Videos and Demos
Share 3–4 HD demo videos at project milestones for official promotion and showcase.
Product Feedback and Suggestions
Submit brief feedback on hardware and API/driver development to help us optimize the product experience.
Academic Social Media Interaction
Tag @ElephantRobotics on Twitter (X), LinkedIn, YouTube, Hacsker or allow our Offical medias to share your research to co-amplify reach.
How It Works
From application to reply in just 5 business days.
1. Online Application
Submit the online application form with your targeted product, project description, and how the arm advances your work.
2. Review & Evaluation
Our team reviews your application within 5 business days to assess your project needs and establish a preliminary proposal.
3. Agreement & Shipping
Sign the formal agreement and complete payment; we will process and ship your hardware immediately upon receipt.
4. Project Delivery
Complete your research and deliver the agreed deliverables as outlined in the cooperation agreement.
Partner Universities and Research Institutions
FAQ
We prioritize Embodied AI, AI Foundation Models, Teleoperation, and Open-Source initiatives. Higher priority is given to projects with publication or GitHub open-source plans.
Sponsored teams receive dedicated online hardware support from our engineering team, including assistance with deployment, setup, wiring, and troubleshooting.
You only need to provide a brief project summary (under 200 words). No core algorithm details or non-public data are required. All submitted information is strictly confidential.
Simply cite Elephant Robotics and the specific hardware model used in your published paper (main text or appendix) or your GitHub repository's README file.
MyArm M&C series and 3-finger grippers are currently available at 50% off. Once your application is approved, we will send you a dedicated purchase link with the discounted price.