In strawberry processing and shipping operations, harvested fruit must be sorted and packaged according to specifications. However, automation is challenging because strawberries vary in size, shape, and color, and are easily damaged. In addition, packaging requires weight control and visual quality assessment. MOTOMAN NEXT uses AI to identify strawberry position, orientation, and quality. It selects the best grasping point for picking, It also considers weight balance and arrangement when selecting and placing fruit, and it can identify out-of-spec products and perform quality inspection. As a result, MOTOMAN NEXT reduces dependence on skilled workers while improving workforce efficiency and ensuring consistent quality in sorting and packaging operations.

While filling and cup-printing processes for food products and other applications are increasingly automated using dedicated equipment, taking out large numbers of cups from boxes and loading them into equipment has remained difficult to automate. Robots must adapt to differences in box conditions and cup shapes, making manual work necessary.
MOTOMAN NEXT uses AI to identify the shape and arrangement of cups inside a box. It autonomously determines the optimal grasping position and picking strategy to ensure stable handling. It can recognize and handle a wide range of cups, including transparent plastic cups, paper cups, instant-food containers, and dessert cups, even when they differ in size, material, and appearance. This flexibility allows it to support high-mix production environments.

In food and chemical plants, workers regularly take raw materials out of cardboard boxes and kraft paper bags and load them into machines. These tasks are common across many industries. However, bags and boxes vary in size and shape, and they can become deformed during transportation or due to moisture, making automation difficult.
MOTOMAN NEXT solves these challenges with AI. First, it uses cameras to recognizes the condition of bags and boxes and determines the most efficient picking sequence. It then analyzes wrinkles and surface features to determine where and how to cut the packaging without damaging the contents and plans the cutting path accordingly. It can also handle deformed cardboard boxes, opening them reliably and loading the raw materials into machines. Tasks that once required human judgment can now be performed autonomously by the robot.

Powder weighing is an essential process in food, chemical, and pharmaceutical manufacturing. However, powder properties vary by material, and even the same powder can change condition over time. This has made automation difficult.
MOTOMAN NEXT uses AI to analyzes the shape and condition of powder. Based on the results, it autonomously determines and performs the optimal scooping motion.
As a result, weighing operations can be performed consistently without relying on operator experience or intuition. MOTOMAN NEXT delivers highly accurate measurements with minimal variation while maintaining stable and repeatable operation.
In addition to helping address labor shortages and reducing workload, MOTOMAN NEXT improves quality consistency and expands automation opportunities in powder-handling processes.

Packaging products into boxes requires careful handling because product size and shape can vary slightly from item to item. This task has traditionally been difficult to automate. The dual-arm AI robot “MOTOMAN NEXT” addresses this challenge.
One of the AI robot’s key features is its human-like body size and joint movement. Using cameras to observe object positions and conditions, the robot coordinates both arms smoothly to perform packaging tasks. It can often be introduced into existing production lines and workstations without major modifications because it can move similarly to a human worker.
MOTOMAN NEXT initially learns from human demonstrations. It then improves through reinforcement learning, becoming more efficient and expanding the range of parts and tasks it can handle.
As labor shortages continue to become a major social issue, the dual-arm AI robot “MOTOMAN NEXT” expands the range of tasks that can be automated by performing delicate tasks traditionally carried out by humans.

Medical instruments used in surgery must be sorted by type before they are cleaned and sterilized. Traditionally, this work has relied on manual labor because surgical instruments such as scissors and forceps vary widely in shape and size and are often mixed together after use. Handling used instruments also exposes workers to infection risks.
One challenge in automating this task is the large number of instrument types, which can exceed 3,000. Another challenge is glare from metal surfaces, which can make camera images difficult to interpret. (This phenomenon is known as halation.) In addition, instruments such as scissors can appear very different when opened or closed, making recognition difficult for conventional robots. The AI integrated into MOTOMAN NEXT addresses these challenges. It can identify the instrument that can be picked easily from a pile, correct glare caused by light reflection for accurate recognition, and recognize instruments accurately whether they are open or closed. MOTOMAN NEXT also determines how to place the instruments in baskets and arranges them automatically. By automating tasks that were once considered possible only for humans, MOTOMAN NEXT reduces both workload and infection risks in medical environments.