Origami Robotics
Origami Robotics builds infrastructure for general-purpose robotic manipulation. Its work focuses on dexterous robot-hand hardware and manipulation systems that improve force transparency, durability and sim-to-real transfer for robots learning real-world object handling.
Market context
Large-scale real-world manipulation datasets remain a major bottleneck for physical AI systems. Origami Robotics aims to close the embodiment gap between human demonstrations and robot execution by aligning human teleoperation hardware with robotic hand kinematics.
Facts
- Website: https://www.origami-robotics.com
- HQ: Millbrae, United States
- Founded: 2026
- Segment: End Effectors
Origami Robotics role in dexterous manipulation hardware
Origami Robotics develops dexterous robotic manipulation hardware designed to improve data collection for robot learning. Origami Robotics builds high-degree-of-freedom robotic hands with integrated in-joint motors and a co-designed teleoperation glove used to capture high-quality real-world manipulation data. Large-scale real-world manipulation datasets remain a major bottleneck for physical AI systems. Origami Robotics aims to close the embodiment gap between human demonstrations and robot execution by aligning human teleoperation hardware with robotic hand kinematics.
- Target environment: Subsea inspection, offshore operations, maritime monitoring, ports, ocean sensing and underwater data-collection workflows.
- Deployment model: Hardware and data-collection model built around robotic hands for physical AI development.
- Customer context: Robot-learning labs, AI developers, manipulation researchers and robotics hardware teams.
- Workflow context: Manipulation hardware, tactile data collection, robot-learning experiments, teleoperation and dexterous grasping workflows.
- Commercial maturity: Early dexterous-manipulation hardware company focused on robot hands and data collection for robot learning.
- Market position: Dexterous robotics company building high-degree-of-freedom robotic hands and data-collection hardware for robot learning.
- Adoption constraints: Adoption depends on durability, dexterity, sensing quality, software integration, cost and evidence of improved learning data.
- Adjacent context: ROVs, AUVs, subsea sensing, offshore inspection, maritime autonomy, ocean data and underwater robotics.
- Source confidence: medium
Team
- Quanting Xie - Co-Founder - Founder row adds context for Origami's hardware-first approach to reducing the embodiment gap in dexterous manipulation.
- Ryan Xie - Co-Founder - Adds founding-team context for Origami's robotic hand and data-collection infrastructure for learning-based manipulation.
Origami Robotics canonical Korthos profile