Force-Controlled Drawing Demo
Shows a robot drawing on a small surface while a nearby computer tracks coordinates and force data in real time.
The demo highlights contact-rich trajectory following where the robot must maintain tool pressure while following a programmed path.
Flexiv
Adaptive Robotics
Use case
drawing
Category
Robot Capabilities And Product Demos
Key capability
force control, trajectory tracking, contact rich manipulation
Storyboard
What the video shows
The storyboard shows a robot drawing on a small surface while a nearby computer tracks coordinates and force data in real time.
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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 drawing.
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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
Force-Controlled Drawing Demo requires repeatable execution in robot capabilities and product demos, where alignment, controlled contact, and process consistency can be difficult to maintain manually.
Value
Operational value
The demo highlights contact-rich trajectory following where the robot must maintain tool pressure while following a programmed path.
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 robot capabilities and product demos 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.