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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Transform your warehouse operations and adapt to scalability demands through cutting-edge robotic automation developed by the foremost AI researchers globally. The Covariant Brain, trained on data from millions of picks across diverse warehouses, allows robots to efficiently and independently select nearly any SKU or product right from the start. Covariant’s AI-driven Robotic Putwall takes this a step further by autonomously organizing items from mixed-SKU containers, effectively bridging labor shortages while enhancing overall throughput. Each implementation is carefully customized to integrate seamlessly with your current floor layout, systems, and both upstream and downstream workflows. Additionally, with fleet learning capabilities, each robot benefits from the collective experience gained through millions of selections made by interconnected robots in warehouses worldwide. This means that as soon as they are deployed, Covariant robots are ready to tackle virtually any SKU or item, irrespective of its shape, size, or packaging. The impact of this technology not only streamlines operations but also significantly boosts efficiency and productivity in your warehouse environment.

Description

Visual Components provides an all-encompassing Robot Offline Programming (OLP) software that enhances and accelerates the programming process for industrial robots from various manufacturers and for a wide range of applications. This innovative platform allows users to design, simulate, and validate robot programs within a virtual setting, which greatly reduces the reliance on physical prototypes and lessens production downtime. Among its standout features are automated path solving that identifies and addresses collision and reachability challenges, realistic simulation with high-quality visual graphics, and broad compatibility with more than 18 post-processors and over 40 robot controllers, accommodating a variety of tasks including welding, processing, spraying, jigless assembly, and part handling. Additionally, the software boasts an intuitive interface, enabling rapid onboarding and effective programming, even for intricate configurations that involve multiple robots and complex assembly processes. This makes it a vital tool for industries seeking to optimize their robotic operations efficiently.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

KUKA.Sim
MotoSim
ROBOGUIDE
RobotStudio
SIMIT

Integrations

KUKA.Sim
MotoSim
ROBOGUIDE
RobotStudio
SIMIT

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Covariant

Founded

2017

Country

United States

Website

covariant.ai/

Vendor Details

Company Name

Visual Components

Founded

1999

Country

Finland

Website

www.visualcomponents.com/products/robot-offline-programming/

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Warehouse Management

3PL Management
Barcoding / RFID
Category Customization
Channel Management
Demand Planning
Inventory Management
Location Control
Order Management
Purchasing
Quality Control
Receiving / Putaway Management
Returns Management
Shipping Management

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