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Robots poised for growth despite Trump's tariff pressure

Chloe Liao, Taipei; Vyra Wu, DIGITIMES Asia 0

Poi-Toong Tang, Asia-Pacific sales vice president at Teradyne. Credit: DIGITIMES

Universal Robots (UR), the global collaborative robot (cobot) leader, maintains optimism for growth despite US President Donald Trump's tariff policies, as advanced manufacturing reshoring could boost demand for automation systems to offset higher American labor costs.

The Danish cobot maker hosted its annual Collaborate event in Taiwan for the first time this year, featuring 22 applications with partners including Nvidia, AI vision specialist Solomon Technology, and industrial automation giant Siemens AG. Taiwan, which ranks fifth in Asia for robot density after South Korea, Singapore, China, and Japan, represents a key growth market.

"Physical AI capable of perceiving and reasoning about the physical world will be the core of the next wave of robotic technology," Nvidia representatives said at the event, discussing platforms including Omniverse, Cosmos, and Isaac.

UR maintains a 40% global market share with 100,000 cobots shipped since 2005, ahead of Taiwan's Techman Robot at about 10%. While Chinese competitors like Dobot and Jaka are gaining ground in the world's largest robot market, UR's two decades of experience and sixth-generation products provide an edge over rivals mostly in their first or second generation.

"Future advanced smart manufacturing systems shaped by robots will center on ecosystems rather than single robotic arms," said Poi-Toong Tang, Asia-Pacific sales vice president at Teradyne, which acquired UR in 2015. The UR+ ecosystem has launched over 500 products.

Despite concerns about trade barriers dampening manufacturing investment, Tang said global demand for automation persists as it remains the ultimate objective regardless of production location. UR introduced its AI accelerator platform at the event, offering developers plug-and-play capabilities to shorten product development cycles through integration with Nvidia's Jetson Orin modules and Isaac acceleration libraries.

Article edited by Jack Wu