Dual Arm Robot

Dual-arm robots are increasingly studied for their enhanced dexterity and ability to perform complex tasks beyond the capabilities of single-arm systems. Current research focuses on improving control algorithms, particularly through deep learning architectures like those incorporating attention mechanisms and population-based training, to enable more robust and adaptable manipulation, especially with deformable objects. This research is driven by the need for more versatile robots in diverse applications, including healthcare (e.g., autonomous swabbing), manufacturing (e.g., cooperative assembly and bin picking), and domestic assistance (e.g., repositioning care), ultimately aiming to improve efficiency and safety in human-robot collaboration.