Robot Deployment Checklist: 12 Steps Before Going Live

Step 1: Conduct a Formal Risk Assessment

Before any robot operates in a new environment, document a formal risk assessment. This is not optional paperwork — it is the foundation of safe deployment. Identify every way the robot could cause harm to people, damage property, or fail in a way that disrupts operations. For each hazard, rate the likelihood and severity, and define mitigations. The risk assessment should be reviewed and signed off by a qualified safety engineer, not just the project team.

Key hazards to address for a collaborative robot arm in a shared workspace: pinch points at joints (especially the wrist and gripper), reach zone incursion by humans, dropped objects from the end-effector, controller failure causing unexpected motion, and communication loss between the robot and control system. Each of these has standard mitigations — safety-rated stop inputs, light curtains, payload limits, and watchdog timers — but the specific combination depends on your environment and risk tolerance.

Step 2: Validate Safety Hardware

All safety hardware must be tested before live operation, not just verified to be present. Test every emergency stop button — the robot must come to a complete, stable halt within the rated stop time. Test any light curtains or area scanners by breaking the beam with a physical object and verifying that the robot stops. Test the force/torque contact detection by applying a gentle force to the end-effector while it is in motion and verifying it triggers the collision response. Document every test with a timestamp and result. Safety hardware that has not been tested is not safety hardware.

Step 3: Prepare and Validate the Physical Environment

The physical environment must match the conditions under which the policy was trained, within the bounds of the policy's demonstrated generalization. Check: lighting levels and color temperature (fluorescent vs LED vs daylight can change apparent object colors dramatically), background clutter (objects behind the workspace that were absent during data collection can confuse visual policies), floor material and friction (relevant for mobile platforms), and the exact positions of fixtures the robot references. If the deployment environment differs from the training environment in any of these dimensions, expect policy performance degradation and plan a re-evaluation cycle.

Mark out the robot's operational zone on the floor with high-visibility tape. Define the exclusion zone — the area humans must not enter when the robot is in autonomous operation — based on the robot's maximum reach plus a safety margin. Install signage at all entry points to the operational zone. If humans will work near the robot during operation (not in a fully fenced cell), define and enforce a formal safe working distance based on the robot's stop time and human approach speed.

Step 4: Validate Policy Performance in Deployment Conditions

Do not assume your lab policy will perform identically in the deployment site. Run a formal evaluation — a minimum of 20 test trials — in the deployment environment before going live. Test across the full range of expected operating conditions: start-of-day when the environment is pristine, mid-shift when the workspace may be more cluttered, and end-of-day when lighting and temperature may have shifted. Record success rate, failure mode distribution, and any safety-relevant behaviors (unexpected collision, out-of-workspace motion).

Define your go/no-go success rate threshold before testing — do not pick it after seeing the results. A reasonable threshold for a first deployment is 85% task success rate in controlled evaluation trials, with zero safety-relevant failure events. If you observe safety-relevant failures at any rate, halt deployment until the root cause is identified and resolved. Use the SVRC benchmarks as a reference for expected policy performance on standard tasks.

Step 5: Set Up Remote Monitoring

A deployed robot that you cannot monitor remotely is a liability. At minimum, set up: a live camera feed accessible to the operations team, joint state and error code logging to a time-series database, an alerting system that pages on-call when the robot enters a fault state, and episode success/failure logging to track policy performance over time. The SVRC platform provides all of these out of the box for systems running the SVRC agent stack, with configurable alert rules and a mobile-accessible dashboard.

Define your escalation path before going live: who gets paged when the robot faults, who has the authority to authorize a restart, and who can perform physical intervention if needed. This chain should be documented, tested, and known to all operators before the first autonomous operation.

Step 6: Train All Operators

Every person who will interact with the robot — operators who monitor it, maintenance staff who will service it, and anyone who works nearby — must receive appropriate training before first operation. Operator training should cover: the robot's operational modes and how to switch between them, how to trigger an emergency stop, how to identify fault states from indicator LEDs or display, what to do (and not do) if the robot stops unexpectedly, and the safety boundaries of the operational zone.

Step 7: Define a Failure Response Playbook

Document exactly what happens when things go wrong. Define a response procedure for each major failure category: policy failure (robot completes task incorrectly), mechanical fault (joint error, gripper fault), sensor failure (camera disconnection, joint encoder error), communication loss, and emergency stop triggering. Each procedure should include who is responsible, what actions to take, and what conditions must be met before restarting. Ambiguity in failure response leads to inconsistent behavior and is a safety risk.

Step 8: Establish a Data Feedback Loop

Deployment is not the end of the data collection process — it is the beginning of a feedback loop that improves policy performance over time. Log every episode with success/failure labels and the robot's joint trajectories and camera feeds. Review failure episodes to identify systematic gaps in the training data distribution. Use identified gaps to plan targeted re-collection: if the policy fails when objects are in the right half of the workspace, collect 50 additional demonstrations with objects specifically placed there.

SVRC's data services include a deployment feedback protocol: we analyze your deployment logs, identify the highest-impact data gaps, and execute a targeted re-collection campaign to address them. This is typically far more efficient than undirected data collection and produces faster policy improvement cycles. Contact our team to set up a deployment monitoring and improvement engagement.

Step 9: Plan for Hardware Maintenance

Establish a maintenance schedule before deployment, not after the first failure. For servo-driven arms like OpenArm: inspect servo cable routing for wear every 30 days, re-torque all structural fasteners every 60 days, and clean camera lenses weekly in dusty environments. Check gripper finger wear every 100 hours of operation — worn fingers change grasp geometry and will degrade policy performance before causing an outright failure. Keep spare servos, gripper fingers, and camera units on-site so maintenance does not require a multi-day parts wait.

Step 10: Define KPIs and Review Cadence

What does success look like, and how will you measure it? Define key performance indicators before going live: task success rate (target vs actual), throughput (tasks per hour), uptime (percentage of scheduled operating hours when the system is available), and mean time to recovery when faults occur. Review these metrics weekly for the first month of operation, then monthly once the system has stabilized. A review cadence without pre-defined KPIs tends to drift toward subjective assessments — "it seems to be working" — that miss gradual degradation.

Step 11: Communicate with Stakeholders

Whoever owns the budget, the physical space, or the operational outcomes of the deployment needs to know what to expect, when to expect it, and how they will be informed of problems. Agree on a reporting cadence — weekly status update during the pilot phase is typical — and define what constitutes a reportable event. Surprises erode stakeholder trust faster than underperformance. If the policy fails more than expected in week one, proactively communicate the root cause and your plan to address it.

Step 12: Plan Your Scale-Up Path

A successful single-robot pilot is only valuable if you know how to scale it. Before going live, document the steps required to replicate the deployment: hardware procurement lead times, operator training time, environment setup requirements, and data collection needs for each additional unit. If scale-up requires additional SVRC support — more data collection, additional hardware through the leasing program, or software integration — align on that plan while the pilot is running. Teams that think about scale-up during the pilot make decisions that support it; teams that wait until after the pilot often discover the current setup was not designed to replicate. Talk to SVRC about your deployment goals and we will help you design a path from pilot to production.