Okamura Corporation will start selling the autonomous mobile robot "ORV," which automates the transportation and alignment of cart trolleys, from September 2022. The ORV is an autonomous mobile robot (AMR) capable of transporting cart trolleys in production sites and logistics warehouses. It generates its own routes and operates without guides, allowing for installation without extensive floor modifications, thereby improving productivity and reducing labor. It automatically recognizes and retrieves cart trolleys, lifts one side of the trolley, and transports it to the destination while avoiding obstacles. Since it is not a towing system, it can turn in place with the trolley and can also move backward, allowing for precise alignment of trolleys even in tight spaces, such as next to EVs or vertical conveyors. The ORV addresses demands for automation without changing the existing operations using cart trolleys, eliminating workplace accidents related to cart trolleys, and solving nighttime labor shortages. It can be utilized for parts supply and transportation between processes within factories using cart trolleys.

We are pleased to announce the release of our pallet storage system, "CybiStar." This product is a pallet storage system that utilizes a shuttle (transport cart) to travel along lanes within the rack, enabling efficient large-scale storage and retrieval of palletized goods. With a simple structure of a level rack and shuttle, it prevents issues such as collisions between pallets, load collapses, and stagnation, ensuring smooth operation and reducing maintenance efforts.

Mitsubishi Logisnext has developed and started selling an unmanned logistics solution for warehouses that combines the laser-guided unmanned forklift "PLATTER Auto" and Okamura's pallet storage system "CYBISTOR." In logistics operations, there are challenges such as a shortage of forklift operators and the need to secure storage space for increasing and fluctuating cargo. To address these issues, Mitsubishi Logisnext, with its experience in unmanned forklift development, and Okamura, which specializes in logistics system equipment such as transport and sorting devices, collaborated to jointly develop this solution. The unmanned logistics solution now on the market integrates Mitsubishi Logisnext's PLATTER Auto, which recognizes its current location by scanning reflectors with a laser scanner, and Okamura's CYBISTOR, where shuttles (transport carts) operate within the lanes of racks to store and retrieve pallet items.

In September 2021, we launched "CybiStar 2," a new model of the pallet storage system "CybiStar," which enables high-density storage of palletized goods by having shuttles (transport carts) run within racks in logistics warehouses. "CybiStar 2" automates the inbound and outbound processes of palletized goods and sorting tasks through a combination of shuttles that move forward, backward, left, and right, along with a lifter (vertical lifting device), significantly reducing the complicated tasks performed by forklifts. Since it does not require aisles for forklifts and allows for high storage using the lifter, the storage efficiency of palletized goods is improved by approximately twice compared to conventional pallet racks, achieving high-density storage. Additionally, operations such as first-in-first-out and first-in-last-out are possible depending on the application.

We have released the latest video of the new model of the robotic piece picking system "RightPick," which performs picking of products and parts in logistics facilities and manufacturing sites. "RightPick" is a robotic piece picking system that collaborates with operators in logistics facilities and logistics system equipment to pick products. It achieves high reliability in automation through a smart gripper, advanced computer vision, control software, and machine learning. The new third-generation model has improved processing speed of the processor, allowing it to operate 20% faster than before and handle a wider range of items. During picking, it realizes more careful, high-precision, and high-density transfer, while also improving operability and maintainability.

The panel structure allows for easy assembly. By consolidating storage on the wall, space can be utilized effectively, and the Kanora series of mobile shelves, which do not require floor anchoring, can be used in various spaces and applications, from offices and stores to factories and logistics warehouses! ■ The "Kanora Slick Rack" is a horizontal type of simple mobile shelf. ■ The "Kanora Dense Stall" is a vertical type of simple mobile shelf. It features a thin rail that combines strength and functionality. The rail is made of aluminum, and a hard steel insert is placed where the V-shaped groove meets the wheels, enhancing durability and ensuring smooth movement. Since floor anchoring with anchor bolts is unnecessary, it is less likely to damage the floor surface and can easily accommodate layout changes or relocations.

Okamura Corporation (Headquarters: Yokohama City, Kanagawa Prefecture, Representative Director: Masayuki Nakamura) will update its robotic piece-picking system "RightPick" for picking products in logistics facilities to a new model, which will be released in June 2021. Okamura signed a partnership agreement with RightHand Robotics, Inc. (Headquarters: Massachusetts, USA, CEO: Yaro Tenzer), the developer and manufacturer of "RightPick," in January 2020 and has been selling "RightPick" since February 2020. "RightPick" is a robotic piece-picking system that collaborates with operators in logistics facilities and logistics system equipment to pick products. It achieves high reliability in automation through smart grippers, advanced computer vision, control software, and machine learning. The new third-generation model has improved processing speed due to enhancements in the processor, allowing it to operate 20% faster than before and handle a wider range of items. During picking, it enables more careful, high-precision, and high-density transfers, while also improving operability and maintainability.