Bin Picking System: What Goes Into One and How to Build It Right

A bin picking system is not a single product. It is a coordinated set of components, camera, vision software, path planner, robot arm, and end-of-arm tool, that work together to locate and retrieve parts from unstructured bins automatically. Get any one of those components wrong and the whole system underperforms or fails entirely.

That is the most important thing to understand before speccing a bin picking cell: the challenge is system integration, not individual component performance. A high-end 3D camera paired with underpowered vision software is a waste of money. A capable vision platform connected to an arm without sufficient reach cannot pick from a deep bin. A well-matched system built from components that were designed to work together deploys faster, runs more reliably, and requires less ongoing maintenance than a collection of individually excellent parts that were not.

This post walks through each component of a bin picking system, what to evaluate at each stage, and how Blue Sky Robotics recommends approaching the build.

Component 1: The 3D Camera

The camera is the sense organ of a bin picking system. Its job is to produce a point cloud of the bin contents accurate enough for the vision software to identify pickable parts and calculate reliable grasp points.

Three properties matter most in camera selection for bin picking.

Point cloud accuracy on difficult surfaces- Metal parts are reflective. Dark rubber components absorb light. Transparent plastic parts scatter it. The camera needs to produce clean, usable depth data on all of these. Industrial structured light cameras, which project a known light pattern and measure its deformation, handle difficult surfaces far better than consumer-grade depth cameras. This is not a place to economize: a camera that loses accuracy on half your parts doubles your failure rate.

Field of view relative to bin size- The camera needs to see the entire bin from its mounting position. Field of view calculators from camera vendors help confirm the right model for your bin dimensions before purchase.

Working distance and depth of field- For deep bins, the camera must maintain accuracy across the full depth range from the top of a full bin to the bottom of an empty one. Check the specified measurement range Z against your actual bin depth before committing to a camera model.

Component 2: Vision Software

The vision software is where the intelligence lives. It takes raw point cloud data from the camera and turns it into actionable grasp instructions: which part to pick, where exactly to grasp it, and at what angle.

Modern bin picking vision software uses a combination of classical computer vision for point cloud processing and deep learning models for part recognition. The deep learning layer matters particularly for parts with complex geometry, parts that look different from different angles, or mixed-SKU bins where the software needs to distinguish between multiple part types in the same pick cycle.

Key evaluation criteria for vision software: Does it handle your specific part geometry reliably out of the box, or does it require custom model training? How much labeled training data does custom training require? Does the software include an integrated path planning module, or does path planning need to be handled separately? And critically: does it have native integration with the robot arm controller you are using, or does it require custom middleware to pass grasp coordinates to the robot?

Mech-Mind's Mech-Vision platform handles 3D vision processing and outputs grasp data, while Mech-Viz handles path planning and robot communication, supporting nearly all major robot arm brands through native integration.

Component 3: Path Planning and Collision Detection

Once the vision software has identified a grasp point, something needs to calculate how the robot arm gets there without hitting the bin walls, the camera mount, surrounding equipment, or other parts in the bin. That is the path planner's job.

Path planning for bin picking is more complex than for open-workspace tasks. The arm is descending into a constrained environment, often at an angle dictated by the part orientation rather than the most convenient approach vector. It needs to retract cleanly after the pick without disturbing remaining parts. And it needs to handle cases where the first-choice grasp point is blocked and fall back to an alternative.

Collision detection runs continuously throughout the motion, updating the trajectory in real time as the arm moves through the bin. This is what prevents expensive arm-on-bin or arm-on-part collisions that damage components or require manual reset.

Component 4: The Robot Arm

The arm executes what the system has planned. Three specifications are non-negotiable for bin picking.

Reach- The arm must be able to descend to the bottom of an empty bin from its mounting position. Account for the full Z-axis travel including the end-of-arm tool length. If the arm cannot reach the bottom 20% of the bin, you will have a persistent empty-bin problem that requires manual intervention.

Six axes - Six degrees of freedom give the wrist the flexibility to approach parts at the angles the vision system specifies, including steeply tilted parts that a 5-axis arm cannot reach cleanly. For bin picking of parts with random orientations, six axes is a hard requirement.

Payload including the gripper- The rated payload must cover the weight of the end-of-arm tool plus the heaviest part being picked. A gripper typically adds 0.5 to 2 kg to the effective payload requirement. Factor this in before selecting the arm.

The Fairino FR5 ($6,999) covers the majority of light-to-medium bin picking applications with a 5 kg payload, 924 mm reach, and full ROS compatibility for vision software integration. For heavier parts, the Fairino FR10 ($10,199) and Fairino FR16 ($11,699) step up payload capacity while maintaining the reach and 6-axis flexibility that bin picking demands.

Component 5: End-of-Arm Tooling

The gripper is the component most often underspecified in a bin picking system. It needs to grasp parts reliably from the angles the vision system will present them at, including approaches that are far from vertical. Vacuum grippers work well for flat-faced parts but fail on curved surfaces and parts with holes. Mechanical grippers handle more part geometries but require more clearance in the bin.

Custom tooling designed around the specific part geometry is worth the investment for high-volume applications. For mixed-part bins, adaptive grippers that conform to object shape extend the range of parts a single end effector can handle reliably.

Getting Started

Use our Automation Analysis Tool to model the ROI of a bin picking cell against your current manual sorting process. The Cobot Selector helps confirm the right arm for your payload and bin dimensions. Browse our full Fairino lineup and UFactory cobots with current pricing, or book a live demo to walk through a system design for your specific application. To learn more about computer vision software visit Blue Argus.

FAQ

What is a bin picking system?

A bin picking system is a coordinated set of hardware and software components, a 3D camera, vision processing software, path planning software, a robot arm, and an end-of-arm tool, that work together to locate and retrieve parts from unstructured bins automatically. The system handles random part orientations, variable bin fill levels, and difficult surface materials without manual sorting or fixturing.

How long does it take to deploy a bin picking system?

For standard industrial parts with good geometry, a basic system can be deployed in days to weeks with modern vision software that uses pre-trained models. Custom part types or complex geometries may require model training and additional tuning, extending deployment to several weeks. Having all five system components specified and integrated from the start, rather than assembled piecemeal, significantly reduces commissioning time.

What is the biggest reason bin picking systems fail?

Mismatched components are the most common cause. A camera that struggles with the part's surface material, vision software that was not designed for the part geometry, or an arm that cannot reach the bottom of the bin all cause persistent failures that are difficult to fix after installation. Speccing the full system together before purchase, rather than optimizing each component independently, is the most reliable way to avoid this.