“As businesses introduce new technologies and components to meet productivity and sustainability goals, we’ve engineered our modular large robot portfolio to enable them to select the best robots and variants to allow them to efficiently undertake their operations” said Marc Segura, President of the Robotics Division at ABB.

“With the most comprehensive portfolio of mechatronic platforms, industrial robots, cobots, and AMRs in the marketplace, the latest robots extend our portfolio even further, helping our customers navigate labour shortages and ensuring they remain competitive, while operating in a sustainable manner.”

ABB’s new IRB 7710 and IRB 7720 robots offer 16 new variants and are ideally suited to support applications across various industries. Operators can choose from a wide range of ABB robots to ensure they have the ideal variant to handle various applications for electric vehicles (EV), hybrid, and traditional car production – spanning from press automation, body-in-white, EV battery construction, and final assembly. These robots are said to be perfect for high payload assembly, such as giga casting, high speed press tending and palletising, as well as high accuracy contact applications, such as machining and friction stir welding.

Powered by OmniCore, the new robots achieve class-leading motion control with path accuracy down to 0.6mm, even with multiple robots running at high speeds of up to 1600mm/s and moving payloads of up to 620kg. Customers can also benefit from an up to 25% reduction in cycle times1 further enhancing productivity and quality.

In the automotive industry, the all-new IRB 7710 with the latest OmniCore controller, will boost the production output of robotic press lines from 12 to 15 strokes per minute to produce 900 parts per hour. Furthermore, in the construction sector, the new robots will support the growth in modular construction, capable of constructing steel building frames and surface finishing, with improvements in speed and quality.

The IRB 7710′s energy efficient design in combination with OmniCore’s regeneration technology achieves up to a 30% energy reduction, while the built-in power pack can relay energy back to the grid.

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Using AI-enabled 3D vision to perform location and mapping functions, ABB’s Visual SLAM AMRs make production faster, more flexible, efficient and resilient while taking on dull, dirty and dangerous tasks so people can focus on more rewarding work.

Visual SLAM combines AI and 3D vision technologies to guarantee a superior performance in comparison to other guidance techniques for AMRs. Said to offer significant advantages over other forms of navigation such as magnetic tape, QR codes, and traditional 2D SLAM that require additional infrastructure to function, Visual SLAM AMRs are being embraced by companies to handle an expanding range of production and distribution tasks.

“Our introduction of Visual SLAM AMRs radically enhances companies’ operations, making them faster, more efficient and more flexible, while freeing up employees to take on more rewarding work,” said Marc Segura, president of ABB Robotics Division. “Offering more autonomy and intelligence, our new AMRs operate safely in dynamic, human-populated environments. Visual SLAM technology provides a new level of intelligence for AMRs that transforms robotic applications, from production and distribution through to healthcare.”

Visual SLAM uses cameras mounted on the AMR to create a real time 3D map of all objects in the surrounding area. The system can differentiate between fixed navigation references such as floors, ceilings and walls that need to be added to the map, and objects such as people or vehicles that move or change position. The cameras detect and track natural features in the environment enabling the AMR to dynamically adapt to its surroundings and determine the safest and most efficient route to its destination. Unlike 2D SLAM, Visual SLAM requires no additional references such as reflectors or markers, saving cost and space and offers accurate positioning to within three millimetres.

By eliminating the need to change the environment, stop production, or add infrastructure, Visual SLAM technology helps to reduce commissioning time by up to 20 percent compared to 2D SLAM, significantly reducing the time needed to introduce a new AMR into the existing fleet. The technology can be used at scale with fleets updated remotely. The technology is also secure, as it analyses raw data only, with no visual images saved on either the AMR or on a server.

ABB developed Visual SLAM AMRs in collaboration with partner Sevensense Robotics, a leading provider of AI and 3D visual technology. The technology is being incorporated in ABB’s latest generation AMRs, the AMR T702V, from Q3 2023, and the AMR P604V, from Q4 2023. These will be followed by other AMR products incorporating Visual SLAM which will be rolled out up to 2025. The Visual SLAM technology is already deployed in industrial projects for customers in automotive and retail, with the potential to replace conventional production lines with intelligent, modular production cells served by AMRs.

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“One of the main problems with high speed 6 axis robots is the flexing of the wrist cables and the damage this can cause which results in down time,” says Neil Billing of AA Robotics. “The VS can now be specified with Ethernet completely through to axis 6 and an additional 7th axis servo cable for a gripper, also through to axis 6.”

The VS series robots can move at speeds of 10,000mm/s carrying loads of up to 7kg and with an assembly accuracy of 0.02mm precision.  Their optional protection class IP67 resists even high pressure washing and cutting chips so the robot can be mounted in the harsh environment of a milling machine.

The optional communication interface with innovative internal wiring allows easy connection of Gigabit Ethernet devices and Servo Grippers directly to the robot flange to avoid the risk of tangled cables and connections. Alternatively using Ethernet I/P node support, remote I/O can be mounted on the robot tooling eliminating cables entirely.

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