Solomon Technology Corp (所羅門) is expanding its artificial intelligence (AI)-powered systems for humanoid robots, with chairman Johnny Chen (陳政隆) saying that the company aims to address one of the biggest hurdles to wider adoption — machine perception. Rather than manufacturing humanoid robots, Solomon develops AI-powered 3D vision modules and machine vision software that enable robots to perceive, understand and interact with their surroundings. The company is also applying the technology to drones, autonomous mobile robots (AMRs) and industrial inspection systems. Photo: CNA In an interview, Chen cited an intelligent drone inspection system for solar farms in southern Taiwan as one of Solomon’s latest commercial applications. Drones equipped with the company’s 3D machine vision and AI software can automatically detect obstructions on solar panels that reduce power generation, he said. The drones identify potential problems during aerial inspections and transmit high-resolution images to maintenance crews, allowing faults to be addressed more quickly and improving the efficiency of solar farm operations, according to Chen. The same AI vision technology has also been deployed in AMRs, robotic arms, pan-tilt-zoom cameras and quadruped robots used in industrial inspection projects in markets including the US and Japan, he said. Humanoid robots must combine three core capabilities to perform practical industrial tasks: reasoning, active perception and action, Chen said. Although advances in large language models and vision-language models have improved robots’ ability to understand instructions, perception remains a major challenge because robots still struggle to identify distant or partially obscured objects in complex environments, he said. To address the problem, Solomon has developed generative AI vision technology that uses synthetic images to train AI models, reducing training time while improving robots’ ability to recognize unfamiliar objects and adapt to different real-world scenarios. The company has also developed an “active perception” system that replaces conventional single-image recognition