o accomplish this, engineers have combined Foundation Models and Reinforcement Learning, which improves Atlas’s flexibility and task execution.
Sequencing requires high dependability. Therefore, Atlas must foresee possible mistakes in the part selection, transportation, or insertion and react appropriately. Unlike robots that need extensive manual programming and human intervention, Atlas operates with greater autonomy, minimizing disruptions and reducing the risk of part damage.
According to the firm, this demand for adaptability led to a complete overhaul of its behavior-authoring system, allowing both humans and AI to create and refine complex manipulation behaviors.
By addressing the challenges of sequencing, Atlas demonstrates its capability as a general-purpose humanoid robot, setting a foundation for broader applications in industrial automation, claims Jackowski in the post.