Sarah Andrzejewski
Product Manager
Software, Yaskawa Motoman
Unlocking Unstructured Environments Through AI Robotics
Traditional industrial robotics has excelled in structured, repetitive manufacturing environments. However, a significant portion of industrial tasks, such as random bin picking, variable assembly, logistics, and material handling in high-mix, low-volume scenarios, remain unautomated due to the complexity and unpredictability of unstructured environments.
Key features discussed will include autonomous adaptivity, allowing the robot to perceive its dynamic surroundings, make human-like judgments, and generate optimal, collision-free paths without being explicitly programmed for every scenario. We will also define AI in robotics and where we see them fitting into the real world. We will present practical examples of Motoman NEXT successfully performing tasks that require human-level perception such as sorting and boxing irregularly placed items, and its ability to operate alongside human workers in flexible, unpredictable workcells.
Track: AI & Smart Automation | Robotics: Applications, Systems, & Innovations
Experience Level: Intermediate
Monday, June 22, 2026
2:30 PM - 3:15 PM CDT
Room: S403ab
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Empowering Students with Motoman NEXT and Physical AI
Track: Education | Robotics: Physical AI
Wednesday, June 24, 2026
10:30 AM - 11:00 AM CDT
A3 NextGen Theater - Booth 32054
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