RobFlow 6.0

RobFlow V6 introduces new capabilities for connectivity, cell insights, vision, and multi-robot control. Key highlights include:

• RobMetrics OEE: Track Availability, Performance, and Quality metrics in RobCo Studio.
• Variable Inspector: Redesigned interface with search, tagging, and multi-select actions.
• Profinet Integration: Control Robots via Siemens PLCs with native Profinet support.
• Workspace Reference Manager: Automatically update poses after Workspace changes.
• Multi-Robot Dashboards: Monitor and control multiple Robots from one interface.
• RobVision Enhancements: Variable assignment, detection-only mode, and visual grasping pose definition.
• Beta Features: Early access to RobCalibration, RobSafety, Streaming Interface, ROS2 Interface and RobVision Label Picking & Depalletizing.

Features

RobMetrics OEE (Overall Equipment Effectiveness)

Introducing RobMetrics OEE, our new system for tracking Robot cell performance and effectiveness directly in RobCo Studio. By capturing and visualizing Availability, Performance, and Quality, it provides actionable insights into operational efficiency.

Key capabilities:

• Automatic metrics tracking: Most events (e.g., production, errors) are logged automatically; you only need to configure a few with the new Event Node in RobFlow.
• Event-driven design: Define events like Blocked, Starved, Good/Bad Counts, or Planned Downtime right in your Flows.
• Comprehensive visualization: See your OEE KPIs in RobCo Studio Dashboards, filter by time range, and export them as CSV.

How to use it: Configure your OEE events in RobFlow with the new Event Node and view your metrics in RobCo Studio under RobMetrics OEE.

Variable Inspector

We’ve completely redesigned how Variables are managed in RobFlow to improve usability, reduce errors, and speed up Flow creation. The new Variable Inspector replaces the old table in the “Change Robot State” drawer with a powerful, dedicated interface.

Key capabilities:

• Tagging and grouping: New tags let you organize Variables and filter them easily (e.g., by use case, Flow, or type). You can also group Variables into folders.
• Expandable overlay: Manage Variables in a full-screen interface instead of the cramped drawer.
• Search and filter: Quickly find Variables by name, type, tags, unused status, or current Flow.
• Node association: View and edit Variables directly linked to specific Nodes.
• Simplified model: Flow Variables are removed—tags now serve as the unified way to organize and reference Variables.

This makes managing Variables across Flows faster, cleaner, and less error-prone.

Profinet Integration

You can now control your RobCo Robot directly from a Siemens PLC via Profinet, with RobCo acting as a Profinet IO-Device (slave). This enables seamless PLC integration for industrial automation use cases.

Key capabilities:

• Robot control via PLC: Start, stop, and move the Robot directly from Siemens PLCs.
• Profinet Variables in RobFlow: Define and sync Boolean, Integer, and Float Variables in RobFlow for use in your PLC logic
• TIA Portal integration: Import the RobCo GSDML, datatypes, and function block for a fast setup.
• Tested environments: Siemens TIA Portal V18/V20 with PLC 1200/1500 series.

How to use it:

1. Import the RobCo GSDML into TIA Portal and add the Robot as a Profinet IO-Device.
2. Connect your PLC to the RobCo Control Unit and assign the correct Profinet device name.
3. Define Profinet Variables in RobFlow and export the .udt file for mapping in TIA Portal.
4. Use the included RobCo function block for reliable communication and state sync.

Note: Our Profinet implementation is tested only on Siemens PLCs. For details, refer to the RobCo Profinet User Manual (https://robco.studio/resources, Technical Data).

Workspace Reference Manager

We’ve added a new Workspace Reference Manager to simplify adapting Flows after Workspace changes. By linking poses to a reference Workspace, you can automatically update all related poses without manually reteaching them.

Key capabilities:

• Define a Workspace by teaching 3 poses, creating a reference plane.
• Update the Workspace by teaching 3 new poses in the calibrated setup—linked poses update automatically.
• Assign movement Nodes to a Workspace using the Reference Node by dragging it over the Nodes to reference.
• Consistent referencing across multiple Flows for faster adjustments.

How to use it:

1. Create a Workspace in Robot Configuration or in the Reference Node.
2. Teach 3 poses to define the initial Workspace
3. If the Workspace changes, reteach 3 new poses.
4. Use the Reference Node to link movement Nodes to this Workspace.

Note: Available for Cartesian poses only (not joint poses).

This removes the need for manual reteaching after shifts or relocations, speeding up deployments and recovery.

Multi-Robot Dashboard Support via iFrame Widget

You can now monitor and control multiple Robots from a single RobFlow Dashboard, improving visibility and reducing operator effort in multi-robot deployments.

Key capabilities:

• Embed multiple Dashboards: Use the new iframe Widget to embed additional RobFlow Dashboards or external URLs directly into a single view.
• Interactive control: Embedded Dashboards are fully interactive, allowing you to perform actions (e.g., Start/Stop) without switching tabs.
• New HTTP call action: Extend the generic button Widget with an on-click HTTP action, letting you trigger commands across multiple Robots with a single click.

How to use it:

1. Add the iframe Widget to your Dashboard and provide the URL of another robot’s Dashboard or relevant external page. Tip: Append ?kiosk to the end of a RobFlow Dashboard URL to display it without the app bar (plain Dashboard view).
2. Optionally configure the generic button to send http calls across multiple Robots.
3. Monitor and control all Robots from a single, unified interface.

This streamlines multi-robot operations, especially for larger cells or customers managing several Robots simultaneously.

RobVision Enhancements

RobVision now gives you more control and flexibility when working with vision solutions:

Key improvements:

• Variable assignment: Assign vision data (e.g., object length, width, number of detections, next picking pose) to Variables for use in your Flow logic.
• Detection-only mode: Run vision detection without triggering Robot movement, letting you process detection results or handle Variables independently.
• UI for grasping pose definition: Define and adjust grasping poses directly on a visualized part for faster, more intuitive setup.

These updates make configuring and using RobVision solutions faster, clearer, and better integrated into your Flows.

Beta Features

With this release, we’re making Beta Features available for the first time. In the Robot Configuration (under Update-Channel), you can now switch between:

• Stable – Default mode with fully supported features.
• Beta – Access to experimental features marked as Beta in the UI.

Important: There is no support for Beta features, and there might be breaking changes in features between Beta and Stable state.

RobCalib: Vision based Calibration (Beta)

Use Vision-Based Robot Calibration to improve your robot’s absolute accuracy, especially for vision-driven use cases. This ensures your robot’s movements precisely match their intended positions, which is essential for reliable vision picking and precision tasks.

Key capabilities:

• Vision-based accuracy improvements: Use RobVision hardware to calibrate your Robot based on camera data, correcting for mechanical tolerances.
• Automated calibration workflow: Collect calibration samples in RobFlow, optimize Robot parameters, and validate results directly.
• Improved precision for vision tasks: Eliminate positional drift and improve accuracy for vision picking.
• Flexible recalibration: Recalibrate after collisions, hardware changes, or relocations.

How to use it:

1. Set up RobVision hardware and open Robot Calibration in RobFlow.
2. Collect ~80–100 samples with the guided calibration Flow.
3. Apply calibration, then verify it by running the detection test in the Validate tab.

For details, see the Robot Calibration Documentation (https://staging.robco.studio/resources, Technical Data).

RobSafety (Beta)

RobSafety lets you configure new safety functions directly in RobFlow, giving you more control over safe Robot operation.

Key capabilities:

• Safe Home: Configure a home position with an allowed tolerance; a safe output is triggered when the Robot is in this position.
• Protective Stop: Assign each of the 4 safe inputs to:
  • Safe Stop 1
  • Safe Stop 2 (manual reset)
  • Safe Stop 2 (automatic reset)
• Safe Joint Limits:
  • Define safe joint position ranges per axis.
  • Set maximum joint speeds individually.
• Safety Space: Create a configurable keep-in box tied to the TCP.
• Relay Output: Use the dual-channel relay to:
  • Mirror the E-stop state.
  • Output whether the Robot is allowed to move (System Stop).

How to use it:

Access RobSafety in the Robot configuration to define limits, assign safe inputs/outputs, and activate safety spaces.

Streaming Interface (Joint & Cartesian) (Beta)

The new Streaming Interface allows you to control your Robot in real time by streaming trajectories directly via UDP, enabling applications like external trajectory planners or dynamic motion control.

Key capabilities:

• Real-time control: Stream joint or Cartesian poses directly to the Robot at high frequency.
• HTTP API integration: Enable or stop streaming mode programmatically via new HTTP endpoints.
• UDP streaming: Send trajectories from a host PC to the Robot controller with low latency and receive real-time feedback.
• Flexible streaming modes:
  • Joint position or joint position & velocity
  • Cartesian poses in the global frame
  • Cartesian offsets relative to the tool frame

How to use it:

1. Connect your host PC to the Control Unit via Ethernet.
2. Enable streaming mode using the HTTP API.
3. Stream target poses via UDP using the provided Python utilities (cartesian or joint space).
4. Stop streaming via HTTP or directly from RobFlow.

For setup details and examples, see the Streaming Interface Documentation (including Python demos for streaming trajectories).

RobVision Label Picking & Depalletizing (Beta)

RobVision now supports image-based training for vision models, allowing you to create picking and depalletizing solutions even when no CAD file is available.

Key capabilities:

• Image-based model training: Upload object or box images to RobCo Studio and label them
• Segmentation: Use AI-assisted segmentation to outline objects, verify or refine masks, and define orientations for accurate picking.
• Label Picking: Train detection models for flat or texture-based objects

How to use it:

1. Open RobVision in RobCo Studio and start the solution wizard.
2. Choose Label Picking (image-based object detection) or Depalletizing
3. Upload images, assign labels, and run the segmentation tool to create accurate masks.
4. Train and deploy your model, then configure the Solution in RobVision in RobFlow

This enhancement eliminates CAD dependency and accelerates setup for vision-based picking and depalletizing tasks.

ROS2 Interface (Beta)

RobCo Robots now provide a ROS 2 interface, enabling integration with the Robot Operating System (currently supporting ROS 2 Jazzy Jalisco). This interface exposes low-level control of the Robot through ROS topics and controllers.

Key capabilities:

• Publish and subscribe to Robot state and command topics via robco\_ros2.
• Build custom control pipelines using ros2\_control.
• Generate URDFs for modular Robot configurations with provided macros.
• Stream joint commands to the Robot once streaming mode is enabled.

Important notes:

• Not installed by default, contact support@robco.de for access.
• Provides low-level control; some safety features may not be available. Always ensure the Workspace is clear of personnel before operating.

For setup instructions, see the ROS 2 Interface Documentation.

Miscellaneous

• Allow Cartesian Pose Variables for all relative Poses in all Pattern Nodes (Stack, Grid, Pallet)
• Improved search function in Test mode (search for In- and Output and general text search)
• Removed Flow Variables
• Default names for Inputs and Outputs (banks and actual IO)
• Improved undo/redo functionality for more stable editing
• Auto-resume Flow when SAFE_STOP_2 is released, if a Flow was running before (can be enabled via feature-flag)

Fixes

• Improved overall system performance and connection stability
• The Advanced Palletizing Node can now handle cases where the Robot and the pallet are not in the same plane
• improved state handling in SAFE_STOP states
• Generic Resume Event Nodes: also resume if paused not on trajectory