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

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.

  1. Step 1

    Prepare the workcell, fixture, part, or target surface shown in the storyboard frames.

  2. Step 2

    Locate and align the robot or tool for drawing.

  3. Step 3

    Execute the task with force control and monitored robot motion.

  4. 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.