Boston Dynamics' Atlas Robot Takes Its First Steps Into Manufacturing

Updated: March 25 2025 23:58
Boston Dynamics has announced that its Atlas humanoid robot is making its way into real-world manufacturing environments. Almost a year after unveiling the redesigned Atlas—described as "faster, stronger, more compact, and less messy"—the company has shared details about how this advanced humanoid robot will begin tackling practical industrial challenges in partnership with automotive giant Hyundai.

While we've seen numerous demonstrations of humanoid robots performing impressive but isolated tasks in controlled environments, Boston Dynamics is now taking concrete steps toward deploying Atlas in actual production settings where it can provide measurable value.



The journey toward creating truly useful humanoid robots requires breaking down ambitious visions into practical applications. In collaboration with Hyundai (which acquired Boston Dynamics in 2021), the company identified part sequencing in automotive manufacturing as the perfect first application for Atlas. This careful selection demonstrates a strategic approach to robotics development—tackling a real-world problem that:

• Is difficult enough to push technological boundaries
• Delivers tangible value that justifies the investment
• Contains elements applicable to broader future applications
• Addresses genuine human pain points in the workplace

Part sequencing might sound mundane compared to the acrobatic feats we've seen from previous Boston Dynamics robots, but it represents a complex logistical challenge within manufacturing environments.

In automotive assembly plants, multiple vehicle models and trim levels move along the same production line. Each vehicle requires specific parts installed in a particular order. Part sequencing is the preparatory process where components arriving from suppliers (typically organized by part type) are rearranged into the exact sequence needed for the vehicles being assembled.

Currently, this process involves human workers who:

• Receive containers filled with single-variant parts from suppliers
• Sort through these parts
• Arrange them onto output dollies in the precise order required for the assembly line
• Transport these sequenced parts to where they're needed

For the initial test application, Atlas is working with engine covers, organizing them from inlet containers into sequenced dollies that will later be positioned alongside the assembly line.



What makes part sequencing particularly suitable for a humanoid robot? The answer lies in its complexity across multiple dimensions that have traditionally resisted conventional automation solutions.

Task diversity presents the first challenge. A complete part sequencing operation involves handling thousands of different components with varying sizes, weights, shapes, materials, handling requirements, and storage configurations. This diversity demands adaptability beyond what specialized automation equipment can typically provide.

Behavior complexity adds another layer of difficulty. Successful sequencing requires a robot to recognize and adapt to different parts, execute varied picking and placing motions, transport items across changing environments, identify when operations don't go as planned, and respond appropriately to unexpected situations. Boston Dynamics has leveraged reinforcement learning and foundation models to build a behavior authoring system capable of handling these complex manipulation tasks without requiring extensive reprogramming for each scenario.

Perhaps most importantly, part sequencing takes place in environments designed for humans, not robots. This means limited visibility into containers where parts are stored, parts positioned at different heights requiring a full range of motion, dynamic surroundings with containers arriving and departing, and no special accommodations to make the robot's job easier.

By deploying Atlas to handle these tasks, manufacturers can potentially reduce workplace injuries, reassign workers to more engaging and less physically demanding roles, improve employee retention, increase throughput and consistency, and enhance overall production efficiency.



What makes this development particularly noteworthy is that Boston Dynamics is moving beyond impressive technical demonstrations to actual industrial deployment. The company has announced that Atlas will begin testing in Hyundai facilities this year, with plans to expand to additional pilot customers.

This marks a crucial shift in the humanoid robotics landscape—from robots that demonstrate capabilities in controlled environments to machines that deliver value in real-world settings. The part sequencing application builds on several technological advances in the Atlas platform: enhanced physical capabilities including strength, range of motion, and dexterity; AI-powered intelligence to understand and adapt to its environment; behavior authoring systems that enable complex manipulation tasks; computer vision to identify and interact with various objects; and learning systems that improve performance over time.

Boston Dynamics appears to be leveraging a combination of traditional robotics techniques alongside newer AI approaches like reinforcement learning and foundation models, creating a hybrid system that balances reliability with adaptability.


The company's approach involves beginning with well-defined, high-value tasks, testing in real production environments, iterating based on real-world feedback, gradually expanding capabilities and applications, and scaling production as the technology proves itself. While the company speaks about Atlas potentially "changing work as we know it," they're grounding that vision in specific applications with clear value propositions.

By moving Atlas from the laboratory to the factory floor, the company focus on part sequencing demonstrates a thoughtful approach to technology development—tackling a specific problem with clear value while building capabilities that will enable broader applications in the future. As Atlas begins testing in Hyundai facilities this year, we'll gain valuable insights into how humanoid robots can effectively integrate into production environments.