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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteThe practical estimate is: runtime in hours ≈ usable battery energy in watt-hours (Wh) ÷ average total power demand in watts (W). To apply it to a route, calculate travel time from distance and a realistic average speed, then add stops, standby, lifting, computing, sensing, communications and other payload loads. Speed, payload and route describe the mission, but they do not determine energy use by themselves. Treat the result as an engineering estimate and validate it with measurements on the actual robot and route.
A single runtime cannot be calculated from the title alone. You also need the robot model, battery configuration, usable state-of-charge range, payload, distance, surface, grades, speed profile, stops, temperature and duty cycle.
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The core battery-life calculation
Start with the energy that the robot can actually use, not merely the battery’s nameplate capacity. Then estimate the robot’s average total electrical demand during the complete mission:
Estimated runtime (h) = usable battery energy (Wh) ÷ average total power (W)
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“Total” includes propulsion and steering plus onboard computers, sensors, networking, safety equipment, payload mechanisms, lights and any other powered accessory. A robot that drives only part of the time may consume substantial energy while stopped, waiting, scanning, lifting or communicating.
For a route, calculate mission duration separately:
Travel time = route distance ÷ representative average speed
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Use the average speed over the route, not the robot’s advertised maximum. Add time for acceleration, deceleration, turns, intersections, slow zones, loading, unloading, docking and deliberate stops. If estimated runtime is shorter than the complete mission duration, the robot needs a larger battery, a lower-demand operating plan, an intermediate charge or a shorter route.
The Carnegie Mellon Robotics Institute’s June 2015 report, Energy Utilization and Energetic Estimation of Achievable Range for Wheeled Mobile Robots Operating on a Single Battery Discharge, models propulsion, steering and robot functions rather than treating travel distance as an energy measurement. Its authors, Xuesu Xiao and William (Red) L. Whittaker, write: “Based on this it points out ways to improve maximum robot traverse range: increasing rover velocity, driving duty cycle (ratio of driving time to total mission time), and decreasing robotics functions’ power.” Read the full report at Carnegie Mellon’s publication page.
Gather the inputs before doing the arithmetic
Usable battery energy
If the manufacturer gives a watt-hour rating, use that as the starting point. If the documentation lists only nominal voltage and amp-hours, calculate nominal energy as:
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Nominal energy (Wh) = nominal voltage (V) × capacity (Ah)
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsNominal energy is not automatically usable energy. The battery-management system may reserve charge to protect the cells, and the manufacturer may specify a maximum depth of discharge. Cold temperatures, battery age, high current, voltage sag and a required emergency reserve further reduce the energy available to the mission. Use the model documentation’s discharge limits and operating guidance rather than applying a universal percentage.
Route and speed
Record the route’s one-way and total distance, the surface, grades, ramps, narrow turns, crossings and areas where the robot must slow down. Build a representative speed profile: loaded speed, unloaded speed, speed in turns, speed on inclines and speed during safety-controlled zones. A maximum-speed specification is not an average route speed.
Payload and configuration
Define the payload mass and its center of gravity, not just the robot’s empty weight. Include a lift, conveyor, pump, arm, refrigeration unit, scanner or other equipment powered by the robot. Payload mechanisms can draw energy while stationary, and a poorly distributed load can increase steering effort or trigger slower motion.
Operating environment
Document floor or ground material, wheel traction, roughness, moisture, incline, ambient temperature and indoor or outdoor operation. Terrain can change both the drive power and the allowable speed. Clearpath’s Husky A300 manual warns that terrain affects stated performance and that payload and incline can affect robot behavior; confirm limits in the target environment.
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- Specify the mission. Write down the route distance, number of trips, payload for each segment, stops, loading and unloading times, lift cycles, docking events, accessory use and the minimum state of charge at which the robot must return or charge.
- Determine usable energy. Take the manufacturer’s battery rating, then apply the documented discharge limit, reserve, temperature restrictions and battery condition. If only voltage and amp-hours are available, multiply them for nominal Wh and clearly label the result as nominal.
- Break the mission into operating states. At minimum, separate loaded driving, unloaded driving and standby. Add lifting, docking, payload operation and auxiliary equipment when they have materially different demand.
- Assign power or drain rates. Use model-specific measurements at the intended payload and conditions whenever available. If the documentation gives current, convert it to power with the relevant voltage; if it gives a percentage of capacity per hour, use that rate only for the stated operating state.
- Calculate energy for each state. For each state, multiply average power by time. Sum all states:
Emission = Σ(Pstate × tstate). Do not count only wheel-running time. - Check the reserve. Compare mission energy with usable energy after the manufacturer’s reserve or discharge limit. The appropriate reserve depends on the battery guidance and the consequence of depletion; no single percentage applies to every robot.
- Validate on the real route. Log starting and ending state of charge or energy, payload, distance, speed profile, terrain, stops, temperature and accessory load during representative runs. Recalculate consumption from those observations and repeat under normal variation.
How speed changes the estimate
Speed affects battery life in two different ways. Faster travel can shorten the time that computers, sensors and communications remain active, increasing the driving duty cycle. However, higher speed can also increase propulsion demand, acceleration losses, tire slip, aerodynamic drag outdoors and stopping energy. The net result depends on the robot’s drivetrain, controller and route.
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Use a representative average for each route segment rather than the top speed. For example, a 1,000-meter loop with a 1 m/s maximum speed does not necessarily take 1,000 seconds: turns, safety zones, crossings and stops may lower the average substantially. If the robot spends half the mission waiting, a drivetrain-only estimate will overstate range even when the moving speed is accurate.
When comparing speed settings, keep payload, terrain, route and stop schedule constant. Measure both energy per hour and energy per meter. A slower setting can consume less power while moving but more energy per completed route because the mission takes longer; a faster setting can do the opposite.
How payload, grades and surfaces change demand
Payload generally raises traction and acceleration demand, especially on inclines, loose ground and rough surfaces. It may also increase steering effort and force the controller to limit speed. The effect is not necessarily proportional to payload mass: wheel traction, gear ratios, tire deformation, center of gravity and the route’s grades all matter.
- Level, smooth floors: rolling resistance and accessory loads may dominate after acceleration.
- Ramps and sustained grades: gravitational work can become the largest propulsion load; the loaded and unloaded cases should be measured separately.
- Rough or soft ground: wheel slip and deformation can increase demand while reducing speed.
- Tight turns and stop-start routes: repeated acceleration and steering events can consume more than a straight, constant-speed route of the same distance.
- Outdoor weather: cold temperatures reduce available battery energy and can alter traction and motor efficiency.
Never apply an unloaded runtime to a loaded mission without evidence that the manufacturer tested both conditions. Confirm payload and incline limits for the exact environment, as recommended in the Husky A300 documentation.
Include every non-driving load
Mobile robots consume energy while they appear to be doing nothing. Navigation computers, cameras, lidar, safety scanners, wireless radios and motor controllers may remain powered during a stop. Add standby time at stations, queueing, traffic waits, docking alignment and scheduled pauses.
Separate powered work from ordinary standby when possible. A lift that runs for 20 seconds per cycle may have a high instantaneous draw but modest total energy; a refrigeration or sensing payload may draw continuously for hours. Calculate each as its own state rather than hiding it inside an optimistic “average driving” figure.
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OMRON notes that auxiliary power draw affects its listed runtime. The relevant specification is the LD / MD / HD Series autonomous mobile robot specification; check the exact model and configuration before using its figures.
Worked example with hypothetical mission data
Suppose a robot has 1,200 Wh of documented usable energy after its operating reserve. A warehouse mission contains 2,400 meters of loaded travel at an observed average of 0.8 m/s, 1,600 meters of unloaded travel at 1.0 m/s, 30 minutes of standby, and 10 minutes of lift operation.
- Loaded travel takes 2,400 ÷ 0.8 = 3,000 seconds, or 0.83 hours.
- Unloaded travel takes 1,600 ÷ 1.0 = 1,600 seconds, or 0.44 hours.
- Standby adds 0.50 hours; lifting adds 0.17 hours.
- Total mission time is approximately 1.94 hours, before any unrecorded delays.
Assume measured average demands for this robot and configuration are 700 W loaded, 500 W unloaded, 120 W in standby and 900 W during lifting. The estimated mission energy is:
- Loaded travel: 700 W × 0.83 h = 581 Wh
- Unloaded travel: 500 W × 0.44 h = 220 Wh
- Standby: 120 W × 0.50 h = 60 Wh
- Lifting: 900 W × 0.17 h = 153 Wh
Total estimated consumption is about 1,014 Wh, leaving roughly 186 Wh of the stated usable energy. These figures are illustrative arithmetic, not a specification for any particular robot. In a deployment, replace every assumed demand with measurements or manufacturer data collected at the actual payload, route and temperature.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What manufacturer runtime figures really mean
Published runtimes are useful reference points only when their test conditions match your mission. The following examples are model-specific specifications, not universal performance statistics:
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| Robot or source | Published battery or runtime figure | Qualification |
|---|---|---|
| Clearpath Husky A300 | 1,024 Wh, 2,048 Wh and 3,072 Wh configurations; listed average operating times of 8 h, 16 h and 24 h respectively | Figures from the current A300 user manual accessed in 2026; publication year is not stated on the page. Verify configuration and operating conditions. |
| MiR600 | Up to 8 h 30 min with maximum payload; up to 11 h without payload | Active operating time published on the manufacturer’s specification page; model-specific and conditional. |
| OMRON LD/MD/HD series | 10 h with no payload; 8 h with full payload | Manufacturer specification dated 2025; check the exact model, test setup and auxiliary power draw. |
| J1600 | Approximately 13% of capacity per hour loaded driving, 12% unloaded and 2% in standby; derived continuous-driving figures of about 7.7 h loaded and 8.3 h unloaded | Preliminary January 2026 data on a page last updated August 3, 2026. The manufacturer says the derived runtimes are indicative, not guaranteed, and they exclude mixed duty cycle, reserve and operating variation. |
For the MiR600 figures, consult the exact MiR600 specifications. For J1600 drain rates and the manufacturer’s assumptions, see the J1600 battery specifications. The A300 battery configurations are documented in the Husky A300 user manual.
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How to compare two robots fairly
Compare both robots against the same mission, not against isolated headline runtimes. Put the following items in a worksheet for each candidate:
| Comparison item | What to record | Why it changes the result |
|---|---|---|
| Usable energy | Wh available within the documented discharge range, including reserve | Nameplate capacity can overstate energy available in service. |
| Payload runtime | Runtime at the intended payload, not only unloaded runtime | Mass, center of gravity and lift equipment alter drive demand. |
| Route profile | Distance, representative speed, starts, turns, stops and grades | Equal distances can require very different mission energy. |
| Environment | Surface, incline, temperature and indoor/outdoor conditions | Traction, rolling resistance and battery performance vary. |
| Non-driving loads | Standby, lifting, sensing, computing, communications and payload power | These loads continue when the robot is stopped or moving slowly. |
| Evidence quality | Measured, calculated or guaranteed figure; test conditions and date | A calculated indicative value should not be treated as a guaranteed field result. |
Clearpath’s Warthog manual gives different nominal runtimes for lead-acid and LiFePO4 configurations. That comparison is meaningful only when the exact battery, payload, terrain and operating context are attached to each number.
Validate the estimate with route data
A short, representative field trial is more valuable than a generic runtime claim. Run the robot with the intended payload and software configuration over the route or a route segment that includes its hardest conditions.
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- Charge the battery according to the manufacturer’s procedure and record starting state of charge, energy or voltage.
- Record payload mass, battery temperature, ambient temperature, route distance, surface, grade and accessory state.
- Log timestamps for driving, stops, standby, lifting, docking and faults. Capture speed if the controller exposes it.
- Record ending state of charge or energy and note any automatic reserve, low-battery mode or speed limitation.
- Repeat enough times to capture ordinary variation, including a cold or heavily loaded case if those conditions occur in service.
- Calculate Wh consumed per mission, per hour and per meter. Use the observed distribution—not only the best run—to set a dispatch or recharge threshold.
Keep the test records with the robot configuration. A software update, new sensor, tire change, battery replacement or payload redesign can invalidate an older estimate.
Common estimation mistakes and fixes
- Using battery capacity alone: divide usable Wh by total average W, and document the reserve and discharge limits.
- Using maximum speed as route speed: measure or estimate segment averages including turns, stops and safety zones.
- Counting only propulsion: add computers, sensors, radios, steering, lifting and payload equipment.
- Applying unloaded runtime to a loaded route: use a loaded test or a manufacturer figure tested at that payload.
- Ignoring standby: model queues, docking, traffic waits and scheduled pauses as separate states.
- Assuming a universal reserve percentage: follow the battery and robot maker’s guidance and the operational consequence of depletion.
- Comparing unlike specifications: identify whether each number is measured, calculated, indicative or guaranteed, and preserve its test conditions.
- Trusting a single ideal run: repeat representative missions and plan around normal variation rather than the best result.
When the estimate is not enough
Do not use a spreadsheet estimate as the sole safety control for a robot that could stop in a hazardous location, block an evacuation route, damage goods or lose temperature control. In those cases, use the manufacturer’s low-battery behavior, automatic return or charging procedures and site-specific risk controls. Confirm that the robot can reach a charger or safe stopping point with the required reserve under the heaviest payload and worst normal environmental condition.
If the model, battery configuration or mission inputs are unknown, the honest output is a calculation plan rather than a runtime number. Once those inputs are measured, the formula is simple; the quality of the answer depends on whether the average demand represents the complete route.
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