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Random part handling

3D robot bin picking systems

Pick components from bins, totes, stillages, pallets or a 3D belt-picking scene without relying on rigid presentation. We integrate 3D image capture, part localisation, grasp selection, robot motion, tooling and recovery as one production cell.

A blue industrial robot arm beside a production fixture.
PresentationRandom or layered parts
Vision3D depth and pose
OutputRobot-ready coordinates

Direct answer

What is 3D robotic bin picking?

A 3D bin-picking system captures the shape and depth of a pile, identifies pickable parts, calculates each part's position and orientation, and guides a robot to a suitable grasp. It is used when components arrive randomly or at different heights and cannot be located reliably from a flat image alone.

01 / Presentation

Start with the real bin, not an ideal sample

Part geometry, surface finish, overlap, entanglement, bin depth and replenishment method determine whether random picking is practical. Representative samples reveal occlusion, reflective surfaces and unstable grasp points before the production concept is fixed.

  • Random, semi-structured or layered presentation
  • Shiny, dark and low-contrast surfaces
  • Topmost-part and accessible-grasp selection
  • Empty-bin, no-pick and difficult-pick handling
02 / Complete cell

Connect perception to a reliable physical pick

A strong point cloud is only the start. Robot reach, collision zones, end-of-arm tooling, approach vectors, grip confirmation and destination accuracy determine whether each vision result becomes a dependable production cycle.

  • Camera-to-robot calibration
  • Grasp ranking and collision-aware grasp and approach planning
  • Vacuum, mechanical or magnetic tooling where suitable
  • Missed-pick recovery and controlled bin change

Decision to action

Engineer the complete production loop.

Each stage is designed against representative products, real timing and the required physical outcome.

01

Scan

Capture usable depth across the accessible bin volume.

02

Locate

Identify the part and calculate up to six degrees of freedom (6-DoF) where required.

03

Plan

Choose a reachable grasp and collision-checked approach.

04

Confirm

Verify the pick and route the part to the next process.

Application opportunities

Where this capability can fit.

Final suitability follows from the product, presentation, rate, environment and acceptance criteria.

Machine loading and stacking
Kitting and order assembly
Cast and machined components
Moulded-part handling
Tote and bin unloading
Fixture or conveyor feeding

Questions manufacturers ask

3D bin-picking questions.

Use these answers to frame the first application review and the evidence needed next.

Can 3D vision pick overlapping parts?

Often, where enough of a part and a valid grasp surface remain visible. Trials should include the most densely packed and difficult presentations, not only separated samples.

Can a bin-picking system handle shiny or black components?

Potentially. Camera technology, exposure strategy, surface geometry and lighting all matter. Representative trials are used to establish whether stable depth data and reliable identification are achievable.

When is 2D vision sufficient instead?

If parts remain on one known plane and only X, Y and rotation vary, a 2D system may be simpler. 3D becomes valuable when height, tilt, overlap or full spatial pose affects the pick.

What happens when no safe pick is available?

The recovery strategy can request another scan, change the view, reposition parts, alert an operator or move to a controlled exception state. The required behaviour is designed into the cell.

Start with the production task

Show us what the system needs to see and move.

Use the project brief form, or email product photos or video with the target output, current layout and required decision. We will define the next technical step.

Measure the last parts in the bin as well as the first

A full bin may offer many easy grasps near the top while the last few components sit against walls, dividers or corners. A successful top-layer demonstration therefore does not establish the useful emptying rate. Include the lower and near-empty states of the actual container in a 3D bin-picking trial.

Record the remaining parts and their positions when no usable pick is found. Distinguish missing depth information, an unrecognised part, an inaccessible grasp and a robot path that cannot reach the proposed pose. Those are different problems and may call for different changes to camera viewpoint, tooling, presentation or recovery. Zivid's technical guidance identifies bin walls and dividers as causes of occlusion in stationary camera arrangements.

Agree the production objective: complete emptying, an allowable residual quantity or a controlled handover for the final difficult parts. Include any operator intervention when calculating useful throughput across a full bin. This makes the performance statement relevant to replenishment and staffing, not only the fastest individual pick. Send the actual bin dimensions, dividers and photographs of parts at the bottom when requesting a feasibility review.

Why test a nearly empty bin separately?

Walls, corners and dividers can hide or obstruct the last parts even when the top layer is easy to pick.

What should be recorded when a bin-picking cell reports no pick?

Record whether the cause is missing image data, recognition, grasp access or robot reach, plus the remaining part positions and required intervention.

Project brief