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About

Sho Tajima is a robotics researcher focused on advancing industrial automation through sensor integration and intelligent motion planning. His primary research areas include bin-picking systems, tactile sensing, and robot assembly automation. Tajima’s most notable contribution is the development of a robust bin-picking system that combines tactile sensors with vision-based template matching, enabling robots to reliably estimate object position and orientation during pick-and-place operations. This work, published in 2019, has garnered 11 citations and addresses a critical challenge in manufacturing automation. In 2020, Tajima further contributed to the field by designing an assembly system that minimizes installation costs and tool-change requirements, achieving 7 citations for its practical approach to cell production. His earlier research (2018) explored robot arm motion generation by learning the relationship between object shape and human motion, laying groundwork for more intuitive robotic task execution. Through these efforts, Tajima demonstrates a commitment to making industrial robotics more adaptable, cost-effective, and sensor-driven—key priorities for next-generation smart factories.