Objective Canvas
Chat on the left. The plan on the right.
Select any passage to refine just that part, use one-click shortcuts for safety, recovery and acceptance tests, and restore any version.
AI-driven Flexible robot programming & commissioning
▶ Run on cell
From objective to production-ready robot tasks. Rapidly.
Describe the outcome, constraints and success criteria. RoboRapid's AI copilot turns them into verifiable robot tasks you can adapt across robot brands, tools and production lines — then commission in the setup that fits, from cloud to fully on-prem.
ROS 2 native · Real-time robot view · UR, KUKA & ABB · Cloud or on-prem models
Assemble the optical valve in under 40 s. Keep contact force below 14 N.
Updated the objective and re-synthesized the policy (v3.0). Insertion uses a force-limited spiral search.
1 · Peg-in-hole spiral search2 · ISO/TS 15066
Add acceptance tests.
Describe what this cell should achieve…↑
Cell 04 · Optical Valve Assembly
v3.0 · AST verified
## Objective
Seat base_chassis, insert optical_core, lock retaining_ring.
## Success criteria
- Cycle time ≤ 40 s per unit
- First-pass yield ≥ 99.0 %
- Placement accuracy ± 0.08 mm (cam_arm)
## Constraints
- Max contact force 14 N
- Collaborative operation · ISO/TS 15066
## Acceptance tests
- [ ] 50 consecutive units without intervention
Built on the open robotics stack
ROS 2
MoveIt 2
ros2_control
Universal Robots
KUKA
ABB
LeRobot
NVIDIA Isaac
How it works
Three steps.
One afternoon.
Stop hand-coding waypoints. Describe what an automated robotic cell should achieve, and let RoboRapid handle the how — transparently.
01
Define the objective
Co-write it with an AI copilot on a live canvas. Ground it in CAD, SOPs, demo videos and cited best practices.
## Success criteria
- Cycle time ≤ 40 s
- Yield ≥ 99.0 %
02
Synthesize the verifiable robot actions
Readable actions, AST-checked in a sandbox and solved with deterministic 4-tier IK in the tool frame.
manip.insert_peg_in_hole(
max_force_n=14.0)
03
Run, record, improve
Execute over ROS 2 and watch every move in the real-time robot view. Each run becomes a synchronized RGB-D and robot-state episode.
episode_0042 · 30 Hz · 2× RGB-D
→ lerobot_v2
Platform
Everything an automated robotic cell needs.
Nothing it doesn't.
Policy-as-code
Read it. Diff it. Trust it.
Real-time robot view
See what the robot sees — as it happens.
Eye-in-hand and overhead RGB-D streams from an electronics assembly cell, side by side with live 6-DoF detections, depth probes and joint telemetry straight from ROS 2.
Perception
Two eyes on every part.
Eye-in-hand and eye-to-hand RGB-D, fused for sub-millimetre alignment and 6-DoF part poses.
Any robot
Bring your arm.
ROS 2 and MoveIt 2 native, through standard ros2_control trajectory controllers.
UR5eKUKA KR6ABB IRB 1200
Any model
Bring your model.
Twelve providers — frontier APIs or fully local weights for air-gapped plants.
CloudOn-premLocal weights
Data flywheel
Every run teaches the next one.
Synchronized dual RGB-D and robot telemetry at 30 Hz, curated and exported to the formats your training stack already speaks.
Export
Open formats only.
LeRobot v2RLDSROS 2 MCAPJSONL + PNG
12
model providers, cloud & local
3
industrial robot families
30 Hz
synchronized RGB-D capture
4-tier
deterministic IK solver
Our principle
Programming an autonomous robotic cell should take an afternoon — not a quarter.
Give your next autonomous robotic cell
an objective.
Open the Studio, describe the outcome, and watch the policy take shape beside it.