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In one of the most complex piece-picking scenarios in warehouse automation, Solwr’s mobile Grab™ robot must pick thousands of SKUs from dynamically updated locations in an unstructured high-activity environment and build stable mixed-SKU pallets - all while maintaining high throughput.
Solwr migrated to Zivid Motion, a global motion planner that computes fast, smooth, and collision-free trajectories for every cycle using 3D input and a continuously changing environment. The system achieves efficient and deterministic robot motion with a straightforward implementation process.
Motion generation is now significantly faster; robot movements are smoother and safer with increased obstacle clearance, and production reliability has improved. The higher number of items picked per hour directly strengthens customer return on investment and enables Solwr to scale its high-performance picking solution.
Zivid Motion planner offers faster computation time, better path, safer path, further away from potentioal obstacles. At the end, it just delivers more items per hour."
Olivier Roulet-Dubonnet, Head of R&D at Solwr Robotics
After installing Zivid 2+ LR110 cameras to the Grab™ robot that can handle transparent plastic-wrapped items, Solwr migrated to Zivid Motion, the new motion planner software from the same machine vision company. They wanted to achieve deterministic, high-speed motion planning and more reliable robot behavior.
Integration was straightforward thanks to a simple and well-documented API, as well as a strong technical support and close collaboration with the Zivid Motion team. The system sends the following inputs to the planner for every cycle:
Because the environment varies, the planner must compute a new collision-free trajectory for every move - something Zivid Motion handles. To optimize performance, Solwr evaluates multiple candidate pick poses and uses list-order prioritization as a reachability filter or the shortest-path selection for maximum efficiency. The result is faster motion generation, smoother trajectories, and increased distance from obstacles, improving both speed and operational safety.
After implementing Zivid Motion, Solwr achieved a clear step change in production performance. Motion plans that previously took several seconds to compute are now generated in a fraction of a second, giving the robot a far more stable and predictable cycle. The resulting trajectories are not only faster but also smoother and safer, with more natural movements and greater distance from surrounding obstacles. This has increased overall system robustness and significantly improved reliability in daily operation.
The higher motion quality and reduced planning time directly translate into more items picked per hour. Because customer return on investment is closely linked to throughput and the number of unexpected stops, every improvement in robot motion immediately increases the value delivered by the system in production.
With faster, more predictable robot behavior and a scalable motion planning foundation, Solwr is now extending the solution to handle larger and heavier objects and to operate in even more unstructured environments. This continued development is carried out in partnership with Zivid, with the shared goal of enabling even faster, safer, and more reliable robotic picking at scale.
