Cobot with gripper above a cluttered pile of metal parts

SEDECO

3D bin picking built to integrate

Affordable industrial 3D sensing, AI pose, grasp definition and robot integration, for applications where premium platforms are commercially hard to justify. Open, configurable, suited to accessible robot platforms. Send an STL or samples; we start a feasibility check.

Scroll · scan

Live stack

RGB, depth and pose, in one view.

Our 3D AI inference sees the bin, fits objects and stages the best grasp for the robot. Camera, integrations and outputs online.

RGB, depth and pose, in one view.

RGB + pose

Axes on every detected part, ready for approach.

Metric depth

Aligned depth map for volume and occlusion.

Robot online

Controller linked, grasp to TCP.

Depth + metrics

See what the camera measures.

Aligned metric depth beside live RGB. Capture, infer and drop timings stay visible, so you know what the stack does on the line.

RGB and depth map with inference metrics
Pick-point coordinate set on 3D model

Grasp tooling

Pick-point on the model, not guesswork.

Choose a point on the detected STL. Position follows every pose; distance runs along the surface normal. Approach direction and cylinder axis stabilize tool orientation.

  • Relative distance along approach
  • Cylindrical axis for symmetric parts
  • Straight to robot TCP

Detect → control

Score objects. Wire the robot.

Found objects inference results
Best match first, score, XYZ and rotation per part.
Robot integrations settings
Integrations online, Fairino XML-RPC or TCP listener.

Cell

Hardware that finishes the grasp.

Fin Ray-style or mechanical fingers, same vision stack, different end effector. Dirty parts, occlusion, pose variation: that is why 3D.

Parallel gripper over the bin
Three-finger gripper on industrial shafts

Pipeline

From STL and point cloud to robot motion.

In-house tooling for training, synthetic data, recursive improvement and grasp selection, wired to the robot.

01

Load STL

CAD as ground truth for fit and grasp.

02

Point cloud

Multi-GigE or Hikrobot 3D, scene to depth.

03

Train the model

Fit under real occlusion and pose variation.

04

Synthetic data

Accelerate learning when labels are scarce.

05

Improve recursively

Feedback until the grasp is dependable.

06

Pickup → robot

Grasp point to controller and PLC handshake.

PoC

STL ready? Samples? Both work.

Workflow: samples or STL → feasibility check → train/configure → robot coupling → commissioning. Ship parts without CAD and constructors can build an STL. Acceptance criteria and support path are agreed up front.

Economically attractive, not universal

We do not position this as a universal replacement for Keyence, Mech-Mind or Pickit. It is a more open, configurable path backed by Sedeco’s machine-vision expertise, performance always subject to feasibility testing on your parts.

Vincent van Montfoort

Ready to empty your bin?

Share STL or samples, robot brand and takt, we’ll propose a PoC path.

Learn before you buy

Start with the knowledge guides when you need to validate feasibility, cycle time or when 3D depth is actually required for robot vision.