Mana: Dexterous manipulation of articulated tools

Researchers at DeepMind developed Mana, a system demonstrating dexterous manipulation of articulated tools—objects with moving joints requiring coordinated multi-step control. The work addresses a persistent challenge in embodied AI: controlling agents to interact with tools beyond rigid object manipulation.

This capability directly affects the scope of tasks accessible to robotic systems. Tools with articulated components (scissors, pliers, keyboards, door handles) represent a significant portion of real-world manipulation tasks. Solving this control problem expands viable deployment domains for robotic agents beyond pick-and-place and basic grasping operations.

For operators, this reduces friction in task design for robotic systems—fewer manual interventions required when agents encounter articulated objects. It also signals feasibility improvements in automation for environments with existing tools and infrastructure, rather than requiring purpose-built rigid tooling. The second-order effect: potential shift in cost-benefit calculations for robotic deployment in unmodified human workspaces, where tool compatibility becomes less of a limiting constraint.