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What is MotoSim?

Yaskawa Motoman's MotoSim EG-VRC (Enhanced Graphics Virtual Robot Controller) is a sophisticated application tailored for offline programming and the three-dimensional simulation of complex robotic systems. This software enables users to design and visualize robotic work cells in a virtual setting, thus removing the need for actual robots during the initial development phases. Key features include the ability to optimize robot and equipment placement, model reach capabilities accurately, compute cycle times precisely, generate paths automatically, identify potential collisions, configure systems, modify condition files, and establish Functional Safety Units (FSU). Additionally, the platform comes with a virtual robot controller that boasts a programming pendant interface closely resembling that of the physical controller, which facilitates a seamless transition from simulated environments to real-world applications. Moreover, MotoSim EG-VRC offers users an extensive library of models, allowing them to download a variety of third-party models that enhance their simulation experiences. This adaptability not only improves the programming process but also significantly speeds up the overall development timeline by enabling thorough testing prior to actual implementation. By leveraging such advanced capabilities, engineers can streamline their workflows and reduce the likelihood of errors in the final deployment of robotic systems.

What is Covariant?

Revolutionize your warehouse operations and meet scalability challenges with state-of-the-art robotic automation, pioneered by leading AI experts across the globe. The Covariant Brain, which has learned from countless selections in a variety of warehouse environments, empowers robots to autonomously and adeptly pick nearly any SKU or product right from the outset. Furthermore, Covariant's AI-driven Robotic Putwall enhances this capability by automatically sorting items from mixed-SKU containers, effectively addressing labor shortages while increasing overall productivity. Each solution is meticulously tailored to fit seamlessly with your existing floor layout, systems, and workflows both upstream and downstream. Moreover, the fleet learning feature enables each robot to gain insights from the shared experiences of interconnected robots operating in warehouses around the world. Consequently, once deployed, Covariant robots are primed to handle nearly any SKU or item, regardless of its dimensions or packaging type. This innovative technology not only simplifies operations but also leads to remarkable improvements in efficiency and productivity within your warehouse setting. As a result, businesses can expect to see a significant return on investment as they embrace these advancements.

Media

Media

Integrations Supported

HAL Robotics
Visual Components

Integrations Supported

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

Windows

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Online Training

Company Facts

Organization Name

Yaskawa Motoman

Date Founded

1989

Company Location

United States

Company Website

www.motoman.com/en-us/products/software/simulation

Company Facts

Organization Name

Covariant

Date Founded

2017

Company Location

United States

Company Website

covariant.ai/

Categories and Features

Categories and Features

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