Realman Robotics Showcases 'Ultra-Lightweight Humanoid' Robotic Arms Robotics & Automation News

RealMan Robotics , a company specializing in the development, production and sales of“ultra-lightweight humanoid robotic arms”, has unveiled its latest robotic arms, joint model and embodied intelligence platforms at Advanced Manufacturing Madrid 2024 in Spain.

At this year's event, RealMan showcased its ultra-lightweight humanoid robotic arms, including the ECO series, RM series robotic arms, WHJ series joint modules, RealEye Vision Sensing Platform, Embodied Intelligence Dual-Arm Development Platform, Embodied Dual-Arm elevation Platform, as well as AI physiotherapy Robot, among other technologies.

The ECO65, which is suitable for industrial applications, is the most advanced robotic arm in the world, and is designed to be used in a variety of applications.

The ECO65 series robotic arm feature a lightweight design and energy-efficient technology, ensuring optimal performance with reduced energy consumption.

It is suitable for a variety of industrial applications, such as assembly, handling, and welding, and can improve productivity and reduce costs.

The RM series, RealMan's flagship ultra-lightweight humanoid robotic arms, boast high speed, precision, flexibility, and reliability.

They are ideal for scenarios such as new retail, smart dining, electronics assembly, and intelligent inspections, significantly boosting productivity while lowering operational costs.

The WHJ series joint modules incorporate innovative technologies and materials, offering high precision, stability, and durability.

These modules maintain reliable performance even in harsh environments, making them suitable for a wide range of robotic and automation applications, delivering flexible and dependable motion control solutions to users.

RealMan's dual-arm embodied intelligence development platform is a state-of-the-art data collection device designed for large embodied models.

Using imitation learning algorithms and a combination of 50 task demonstrations with static data training, it can achieve a task success rate of up to 90 percent.

The standard configuration includes dual main arms for operation, a passive secondary arm, a global camera for object recognition, and a localized camera mounted on the secondary arm.

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