LR Mate 200iD/7L

About

About LR Mate 200iD/7L

LR Mate 200iD/7L is a six-axis compact industrial robot with a seven-kilogram payload and 911-millimetre reach. Its long-arm geometry expands access to machines, conveyors and fixtures while maintaining a small mounting footprint.

The arm supports assembly, machine tending, inspection, dispensing and small-part handling. FANUC controllers provide integrated vision, force sensing and production communications, while floor, wall and inverted mounting options support different cell layouts. The wrist and arm are available with environmental protection for industrial use.

Capabilities

Source-backed capabilities

  • Tactile interaction sensing

    Research demonstration - 2023-08-06 - Demonstrated textile tactile skins for human-robot interaction on the LR Mate 200iD/7L. - environment: industrial human-robot interaction experiment

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  • Force-controlled manipulation

    Demonstrated - FANUC documents LR Mate 200iD/7L robots using vision and force sensing to assemble over-moulded electrical connectors in a customer-supplied production example.

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  • Robotic assembly

    Demonstrated - FANUC documents LR Mate 200iD/7L robots using vision and force sensing to assemble over-moulded electrical connectors in a customer-supplied production example.

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Research

  • Simulation-aided Learning from Demonstration for Robotic LEGO Construction

    2023-09-20 - Research Publication - To address the challenges, this paper presents a simulation-aided learning from demonstration (SaLfD) framework for easily deploying LEGO prototyping capability to robots.

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  • A Lightweight and Transferable Design for Robust LEGO Manipulation

    2023-09-05 - Research Publication - Lego is a well-known platform for prototyping pixelized objects. However, robotic Lego prototyping (i.e., manipulating Lego bricks) is challenging due to the tight connections and accuracy requirements. This paper investigates safe and efficient robotic Lego manipulation. In particular, this paper reduces the complexity of the manipulation by hardware-software co-design. An end-of-arm tool (EOAT) is designed, which reduces the problem dimension and allows large industrial robots to manipulate small Lego bricks. In addition, this paper uses evolution strategy to optimize the robot motion for Lego manipulation. Experiments demonstrate that the EOAT can reliably manipulate Lego bricks and the learning framework can effectively and safely improve the manipulation performance to a 100% success rate. The co-design is deployed to multiple robots (i.e., FANUC LR-mate 200id/7L and Yaskawa GP4) to

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  • Customizing Textile and Tactile Skins for Interactive Industrial Robots

    2023-08-06 - Research Publication - Tactile skins made from textiles enhance robot-human interaction by localizing contact points and measuring contact forces. This paper presents a solution for rapidly fabricating, calibrating, and deploying these skins on industrial robot arms.

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  • Robotic LEGO Assembly and Disassembly from Human Demonstration

    2023-05-25 - Research Publication - To satisfy individual needs and self-sustainability, this paper presents a framework that learns the assembly and disassembly sequences from human demonstrations.

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  • Task-Agnostic Adaptation for Safe Human-Robot Handover

    2022-09-20 - Research Publication - Human-robot interaction (HRI) is an important component to improve the flexibility of modern production lines. However, in real-world applications, the task (\ie the conditions that the robot needs to operate on, such as the environmental lighting condition, the human subjects to interact with, and the hardware platforms) may vary and it remains challenging to optimally and efficiently configure and adapt the robotic system under these changing tasks.

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  • Safe Interactive Industrial Robots using Jerk-based Safe Set Algorithm

    2022-04-06 - Research Publication - The need to increase the flexibility of production lines is calling for robots to collaborate with human workers. However, existing interactive industrial robots only guarantee intrinsic safety (reduce collision impact), but not interactive safety (collision avoidance), which greatly limited their flexibility.

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  • Learning Variable Impedance Control via Inverse Reinforcement Learning for Force-Related Tasks

    2021-02-13 - Research Publication - Although many approaches based on deep reinforcement learning (RL) and learning from demonstration (LfD) have been proposed to obtain variable impedance skills on contact-rich manipulation tasks, these skills are typically task-specific and could be sensitive to changes in task settings.

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Resources

Media library

Official FANUC documentation and exact manufacturer-hosted imagery for the LR Mate 200iD/7L long-reach industrial robot.

Timeline

  • RTSS integrated two FANUC LR Mate 200iD/7L robots into Thogus' helmet-drilling cell, increasing…

    2026-07-16 - Deployment - Two FANUC LR Mate 200iD/7L robots operate in the Thogus helmet-drilling cell. The installation increased output by about 25%.

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