Robotic Therapy Development
Shows a therapy development setup where a robot follows marked body landmarks on a mannequin while an operator supervises from a tablet interface.
The workflow demonstrates rehabilitation research with controlled contact force, body mapping, and repeatable treatment-path execution.
Flexiv
Adaptive Robotics
Use case
robotic therapy
Category
Healthcare And Service Robotics
Key capability
force control
Storyboard
What the video shows
The storyboard shows a therapy development setup where a robot follows marked body landmarks on a mannequin while an operator supervises from a tablet interface.
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Step 1
Prepare the workcell, fixture, part, or target surface shown in the storyboard frames.
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Step 2
Locate and align the robot or tool for robotic therapy.
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Step 3
Execute the task with force control and monitored robot motion.
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Step 4
Confirm the placement, contact path, inspection result, or finished surface before repeating the cycle.
Challenge
Why this task is difficult
Robotic Therapy Development requires repeatable execution in healthcare and service robotics, where alignment, controlled contact, and process consistency can be difficult to maintain manually.
Value
Operational value
The workflow demonstrates rehabilitation research with controlled contact force, body mapping, and repeatable treatment-path execution.
Deployment layer
How Robita AI helps
Robita AI turns this kind of Flexiv demonstration into a deployment plan: we assess the manual workflow, define the tooling and fixture assumptions, validate the robot capability, and map the pilot path from first test to production rollout. For healthcare and service robotics applications, that means connecting the visible robot motion to practical questions like cycle time, safety, operator handoff, data capture, and integration with the existing workstation.
Complexity reduction
How Flexiv force control reduces complexity
Flexiv force control lets the robot adapt during contact instead of relying only on exact position commands. That reduces the need for heavy custom mechanics, perfectly rigid fixtures, and long exception programming because the robot can feel insertion, pressure, and surface contact while it works.