Stability Against Disturbance
Shows a robot holding a task position while a person physically pushes and disturbs the arm, then recovering back to the intended pose.
The demo highlights compliance and disturbance rejection for tasks that must remain stable despite unexpected contact.
Flexiv
Adaptive Robotics
Use case
disturbance rejection
Category
Robot Capabilities And Product Demos
Key capability
compliance, force control
Storyboard
What the video shows
The storyboard shows a robot holding a task position while a person physically pushes and disturbs the arm, then recovering back to the intended pose.
-
Step 1
Prepare the workcell, fixture, part, or target surface shown in the storyboard frames.
-
Step 2
Locate and align the robot or tool for disturbance rejection.
-
Step 3
Execute the task with compliance and monitored robot motion.
-
Step 4
Confirm the placement, contact path, inspection result, or finished surface before repeating the cycle.
Challenge
Why this task is difficult
Stability Against Disturbance 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 compliance and disturbance rejection for tasks that must remain stable despite unexpected contact.
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.