KORTHOS / ECOSYSTEM / PRODUCT

UFACTORY xArm 7

About

About UFACTORY xArm 7

UFACTORY xArm 7 is the seven-degree-of-freedom member of the xArm line, using its redundant joint to reach around obstacles and adopt alternative poses within a 700 mm workspace. The arm carries 3.5 kg, weighs 14.3 kg and is specified at ±0.1 mm repeatability with a maximum tool speed of 1 m/s. That combination supports research, vision-guided manipulation and light industrial tasks.

UFACTORY Studio provides graphical programming, hand teaching, trajectory recording and offline task setup. Python, ROS, ROS 2 and simulation interfaces support custom applications, while collision detection, self-collision avoidance and configurable safety boundaries assist integration. Tooling, speed, payload, risk assessment and cell design determine the required safeguarding for each application. UFACTORY sells the arm directly with controller choices and optional grippers, force/torque sensing and other accessories.

Observed use

Exact-product configurations are shown without inferring supply, purchase, customer status, standard fit, deployment or partnership.

  • Sharpa Wave

    Research Experiment - Mounted - Physical - FINGR used a Sharpa Wave hand mounted on an xArm7 for autonomous 2×2 cube turns and solves, with marker tracking and table-assisted regrasping.

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Research

  • Embodied Playground: A Long-Horizon Agentic Robotics Benchmark for Physical, Strategic, and Spatial Reasoning

    2026-10-19 - Research Publication - Embodied Playground tests long-horizon robotic reasoning across 410 simulated task environments. Its EP-100 subset contains 100 tasks in five suites and 16 task types, with separate goal, rule-compliance and physical-validity checks. The research team includes Sharpa and university affiliations.

    Source
  • Beyond the End-Effector: Learning Whole-Arm Contact Manipulation from Human Demonstrations

    2026-10-13 - Research Publication - WACL transfers human demonstrations into whole-arm contact manipulation, including tasks with constrained end-effector objectives. Physical evaluations use UFACTORY xArm 7 and zero-shot transfer to Franka Research 3.

    Source
  • FINGR: Learning Dexterous Hand Control for Real-World Rubik’s Cube Solving

    2026-09-27 - Research Publication - UC San Diego’s FINGR learns contact-rich finger control from demonstrations using finger-relative geometry and future-interaction prediction. Physical evaluation uses a Sharpa Wave hand on an xArm7, with coded-marker cube tracking and table-assisted regrasping.

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Context

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