Robotic laser cladding provides a flexible solution for repairing and strengthening components with complex curved surfaces. Unlike flat plates or simple cylindrical parts, components such as screw pump rotors contain continuously changing curvature and surface normals. A robot must therefore control not only the position of the laser cladding head, but also its orientation, working distance, track spacing and motion continuity.

A 2025 study published in China Surface Engineering investigated this problem using a screw pump rotor as the representative complex-surface component. The researchers combined reverse engineering, 3D surface reconstruction, laser cladding path planning, robot kinematics, offline simulation and experimental validation. The results showed that properly planned robotic trajectories could produce smooth cladding surfaces with good overlap even in regions where curvature changed significantly.

This article explains the key engineering principles behind robotic laser cladding for complex surfaces and how path planning affects coating quality.

Why Is Laser Cladding on Complex Surfaces Difficult?

Conventional laser cladding on a flat surface can follow relatively simple linear or raster paths. Complex three-dimensional components are different because the geometric relationship between the laser head and workpiece changes continuously.

Continuously Changing Surface Curvature

Complex surfaces may contain convex, concave, twisted or spiral regions. As the laser head moves across these areas, the radius of curvature changes.

The path therefore needs to follow the actual surface geometry rather than simply move in fixed X, Y and Z directions. This is one reason multi-axis robotic systems are useful for complex-surface laser cladding.

Changing Surface Normal Direction

Surface orientation is equally important.

The study notes that the laser beam direction should, as far as possible, coincide with the surface normal at the scanning point. Because the normal direction changes continuously across a complex surface, the laser head pose must also change along the path.

Maintaining Stable Track Overlap

A large surface is normally covered by multiple adjacent cladding tracks. Their spacing directly affects the final surface profile.

If overlap is too small, depressions can form between adjacent tracks. If overlap is excessive, material accumulates in the overlapping region and the coating becomes progressively higher. An appropriate overlap produces a much flatter multi-track cladding layer.

What Is Robotic Laser Cladding?

Robotic laser cladding combines a laser deposition system with a multi-axis industrial robot. The robot controls the relative position and orientation between the workpiece and laser processing head while the laser melts the supplied material and a thin region of the substrate.

For simple parts, a conventional CNC motion platform may be sufficient. For complex curved components, a six-axis robot provides additional orientation freedom, allowing the process to follow surfaces whose normal direction changes continuously.

The technology is particularly relevant to repair and remanufacturing because material can be deposited only where it is required.

Why Use a 6-Axis Robot for Complex Surface Laser Cladding?

The main advantage of a six-axis robot is its ability to control both position and orientation.

Instead of merely moving the laser head from one XYZ coordinate to another, the system can adjust its pose to follow a three-dimensional surface. This provides greater flexibility for components with irregular geometry.

However, additional degrees of freedom also make trajectory planning more complicated. Each target pose must correspond to a valid robot configuration, remain within joint limits and avoid singular configurations. The study therefore combined surface path planning with forward and inverse robot kinematics before performing the actual cladding experiment.

Robotic Laser Cladding Workflow for Complex Surfaces

A practical workflow derived from the study can be summarized as:

3D scanning → point cloud processing → surface reconstruction → cladding path generation → path discretization → surface normal estimation → laser head pose calculation → trajectory smoothing → robot simulation → laser cladding

The important point is that complex-surface cladding begins before the laser is switched on. Accurate geometric data and reliable motion planning are prerequisites for stable deposition.

3D Scanning and Reverse Engineering

Point Cloud Data Collection

When an accurate digital model of a repair surface is unavailable, reverse engineering can be used.

In the study, a 3D laser scanner collected surface data from a screw pump rotor. The resulting point cloud represented the actual geometry of the complex helical surface.

STL Surface Model

The point cloud was converted into an STL model consisting of triangular facets.

Because scanned STL data can contain defects and redundant information, the researchers repaired the mesh and simplified unnecessary data before using the model for path planning.

NURBS Surface Reconstruction

The processed data was then fitted using NURBS surfaces and converted into a solid model.

Comparison between the reverse-engineered model and the standard model showed an overall error within ±0.15 mm in this study.

This accuracy is important because geometric errors introduced during scanning and reconstruction can ultimately affect the calculated cladding trajectory.

Generating the Initial Laser Cladding Path

Surface Slicing

After obtaining the digital surface, the next step is generating the deposition tracks.

The researchers used a group of equally spaced parallel cutting planes to slice the STL surface. The spacing between these planes corresponds to the distance between adjacent cladding tracks.

Cutting Plane and STL Mesh Intersection

Each cutting plane intersects the triangular surface mesh at multiple points. Connecting these intersection points in the correct sequence creates the initial laser cladding path.

This approach converts a complicated three-dimensional surface into a series of processable cladding trajectories.

Controlling Laser Cladding Track Overlap

Track overlap is closely related to the final coating profile.

Insufficient Overlap

When the distance between tracks is too large, valleys or depressions can remain between neighboring beads. The coating may therefore have poor surface continuity.

Excessive Overlap

When tracks are too close together, excessive material accumulates in the overlapping area. This can increase coating height and reduce surface uniformity.

Proper Track Overlap

With appropriate spacing, neighboring beads combine to create a relatively flat cladding surface.

The study established a theoretical overlap model based on single-track width, height, track spacing and overlap ratio.

For industrial processing, the appropriate overlap should therefore be determined together with the actual bead geometry rather than treated as an isolated setting.

Complex Surface Path Discretization

A continuous three-dimensional curve cannot simply be transferred to a robot controller as an infinitely continuous path. It must be represented by interpolation points.

Chord Height Error

The distance between the mathematical curve and the straight segment connecting neighboring interpolation points creates a chord-height error.

Smaller errors allow the discrete trajectory to reproduce the original curved surface more accurately, but path planning must also remain practical for robot execution.

Path Planning for Large Curvature Changes

The paper points out limitations of the conventional equal-chord-height-error approach when surface curvature changes significantly.

It therefore proposes an isometric curve tangent method based on equal chord-height error to discretize the cladding path. The resulting interpolation points are then used for subsequent pose and robot trajectory calculations.

Surface Normal and Laser Head Orientation

Position alone is not sufficient for complex-surface laser cladding. Each interpolation point also needs an orientation.

Surface Normal Estimation

The study estimates the normal vector by fitting a local plane to neighboring surface points. The normal of this fitted plane is used as the estimated surface normal at the interpolation point.

Local Coordinate System

A local Cartesian coordinate system is then established for each point.

The Z-axis follows the surface normal, while the X-axis is determined by the direction from the current interpolation point toward the next point. The Y-axis is calculated from the X- and Z-axis directions.

Laser Head Pose Calculation

Combining the position of an interpolation point with its local coordinate system provides the complete pose required for robot trajectory planning.

This enables the laser head to continuously change orientation as it travels across the curved surface.

Maintaining Laser Head Stand-Off Distance

The laser head cannot physically follow the surface coordinates themselves.

A defined offset must be applied along the surface normal so that the processing head remains at the required distance from the workpiece. The study therefore extends the laser-head position outward along the normal direction when calculating its pose.

Maintaining a stable stand-off relationship is especially important when the surface height and orientation change continuously.

Smoothing the Robot Laser Cladding Path

Problems with Point-to-Point Motion

Direct point-to-point motion can cause abrupt changes in robot end-effector pose at interpolation points.

The study identifies this as a potential source of vibration during laser cladding.

Arc Transition and Smooth Motion

To address this problem, circular transition segments were inserted between neighboring trajectory sections.

The original path was therefore transformed into a combination of straight lines and arcs. Simulation showed that this method enabled smooth transitions between interpolation points.

Smooth motion is particularly important for laser cladding because abrupt robot movement can disturb the relationship between scanning speed, deposition position and neighboring tracks.

Robot Kinematics for Laser Cladding

Forward and Inverse Kinematics

Forward kinematics calculates the position and orientation of the robot end from known joint angles.

Inverse kinematics solves the opposite problem: determining joint angles that produce the required laser processing pose.

For complex-surface cladding, inverse kinematics is essential because every planned surface point must be converted into executable robot motion.

Joint Limits and Singularity Avoidance

Not every theoretical tool pose can necessarily be reached safely.

The robot must remain within its allowable joint ranges and avoid singular configurations. The paper verified its forward and inverse kinematic models before using them for trajectory planning.

Coordinate System Calibration

Robotic laser cladding involves several coordinate systems, including the robot base, robot end, flange, workpiece, interpolation point and laser head.

Correct transformations between these coordinate systems are necessary to convert the calculated surface trajectory into actual robot movement.

Before simulation, the study also aligned the robot base coordinate system, flange/tool coordinate system, workpiece coordinate system and processing coordinate system to reduce errors caused by incorrect position or orientation.

Offline Simulation Before Laser Cladding

Offline simulation allows the planned trajectory to be evaluated before actual processing.

Robot Reachability

The complete trajectory should first be checked to confirm that all required positions are reachable.

Joint Limit and Singularity Check

The study used PQart offline programming software to simulate the trajectory. For its specific test path, the simulation reported no unreachable positions, joint-limit errors or singularities.

Robot Program Generation

After successful simulation, the planned trajectory was post-processed into executable robot machining code.

The robot model was also analyzed in MATLAB/Simulink to evaluate joint angular displacement, velocity and acceleration. Joint-angle changes remained continuous during the simulated process.

Laser Cladding Equipment for Complex Curved Surfaces

The experimental system described in the study consisted mainly of a fiber laser, powder feeder, laser cladding head, water chiller, control system and six-axis serial robot.

For complex-surface applications, these components must work as an integrated system. The robot controls spatial motion, while the laser, powder feeding and processing head establish the deposition process.

The required configuration depends on component geometry, dimensions, base material, cladding material and repair area.

Experimental Validation on a Screw Pump Rotor

The researchers performed actual laser cladding experiments after completing trajectory simulation.

Substrate and Cladding Material

The experiment used 45 steel as the substrate and Fe90-2 iron-based alloy powder as the cladding material.

The powder contained Fe as the balance, with 14 wt.% Cr, 1.3 wt.% Si, 0.3 wt.% C and up to 1 wt.% each of Mo and Mn.

Experimental Process Parameters

After multiple process tests, the study selected a set of parameters including:

These are case-specific experimental values, not universal settings for robotic laser cladding. The paper’s table also reports a scanning-speed value whose unit is not consistent with the earlier trajectory-simulation description, so it is not reproduced here as a general process reference.

Cladding Results

During the actual experiment, the robot moved continuously along the planned trajectory without joint-limit or singularity errors.

The resulting cladding layer showed relatively uniform thickness, a smooth overall surface, low waviness and good forming quality. The researchers also reported good overlap in regions with significant curvature changes.

How Path Planning Affects Laser Cladding Quality

For complex components, path planning and laser cladding parameters cannot be treated as completely separate problems.

The planned trajectory determines:

• where each cladding track is deposited;
• the distance between neighboring tracks;
• laser-head orientation;
• motion continuity;
• the relationship between the head and curved surface.

A geometrically inaccurate or discontinuous trajectory can therefore affect overlap and surface uniformity even when the laser parameters themselves are suitable.

The experimental results of this study demonstrate why robotic laser cladding requires both process control and motion control.

Key Factors for Stable Robotic Laser Cladding

A stable complex-surface process requires accurate surface reconstruction, appropriate track spacing and overlap, reliable surface-normal estimation, correct laser-head orientation and stand-off distance, smooth robot motion, accurate coordinate calibration, offline trajectory verification and suitable laser cladding parameters.

These factors are interconnected. Improving only one part of the system does not guarantee a stable result if geometry, robot motion or deposition conditions are poorly matched.

Applications of Robotic Laser Cladding for Complex Components

The experimental work focused on a screw pump rotor, demonstrating the relevance of robotic cladding for helical and strongly curved surfaces.

The same path-planning principles are relevant to other components where the processing surface changes continuously, such as blades, irregular rotors, molds and other complex repair or remanufacturing parts. These broader applications should be evaluated individually because component geometry, accessibility and process requirements differ.

Challenges of Complex Surface Laser Cladding

Complex-surface robotic cladding still requires careful engineering. Accurate surface reconstruction is necessary before trajectory generation, while rapid curvature changes increase the difficulty of maintaining correct orientation and track spacing.

The robot must also have sufficient reach and freedom of movement without exceeding joint limits or entering singular configurations. At the same time, the planned trajectory must remain smooth enough for stable processing.

For this reason, complex-surface laser cladding should be considered an integrated problem involving geometry, path planning, robot motion and laser deposition parameters rather than simply a conventional cladding process mounted on a robot.

Future Development of Robotic Laser Cladding

Future development will increasingly focus on improving the integration between surface geometry and robotic processing.

More automated surface reconstruction and path generation could reduce programming effort for irregular repair components. Improved calibration and simulation can further reduce differences between digital trajectories and actual robot motion.

For industrial remanufacturing, the broader goal is a more integrated workflow in which component geometry can be captured, the repair region reconstructed, the cladding trajectory generated and verified, and the final robot program prepared with less manual intervention.

Conclusion

Robotic laser cladding for complex surfaces requires much more than moving a laser head along a three-dimensional curve. Surface geometry must first be accurately reconstructed, after which the cladding tracks, interpolation points, surface normals and laser-head poses can be calculated.

Track overlap must be controlled, abrupt trajectory transitions should be smoothed, and robot kinematics must be checked for reachability, joint limits and singularities. Offline simulation provides an additional verification stage before actual laser processing.

The screw pump rotor study demonstrated that this integrated approach can produce smooth robotic motion and good multi-track cladding quality on a surface with substantial curvature variation. The proposed path-planning method kept the maximum chord-height error within the specified target range, while the experimental coating showed relatively uniform thickness, low waviness and good overall forming quality.

For complex component repair and remanufacturing, combining reverse engineering, robotic path planning and laser cladding provides a practical route toward automated processing of geometries that are difficult to handle with simple fixed-axis motion systems.