Robot Accuracy: Understanding the Gap Between Repeatability and Absolute Precision

Fraunhofer Institute for Manufacturing Engineering and Automation (IPA) is addressing the critical issue of robot accuracy in industrial applications, revealing why many robots excel at repeatability but struggle with absolute accuracy.

The Accuracy Challenge in Industrial Robotics

Industrial robots typically demonstrate excellent repeatability (around 0.1 mm), meaning they can perform the same task multiple times with nearly identical results. However, their absolute accuracy—how precisely they reach spatial coordinates relative to their base system—often ranges between 0.5 and 1.5 mm, significantly lower than their repeatability performance.

This accuracy gap creates substantial challenges in various manufacturing scenarios, particularly in applications requiring precise positioning such as welding, pick-and-place operations, overspray-free painting, and drilling.

Impact on Manufacturing Efficiency

Poor absolute accuracy particularly affects:

Small batch production where processes aren’t identically repeated
Welding quality, where deviations of just tenths of a millimeter can lead to rejections
Offline programming (OLP), where programs created in simulation require time-consuming corrections when transferred to real robots

These limitations result in increased machine downtime, reduced production efficiency, and in some cases, prevent robots from being used for certain applications altogether.

Root Causes of Inaccuracy

The Fraunhofer IPA team identifies three main categories of accuracy problems:

Hardware-related: Design limitations including inferior encoders, gears, or insufficient rigidity
Software-related: Poor calibration and insufficient controller performance
External factors: Environmental conditions (temperature, air pressure) and process forces

For increasingly common “closed-loop” robotic systems that incorporate sensors to detect the environment, additional challenges arise from poor sensor data or suboptimal component interaction.

Fraunhofer’s Diagnostic Approach

As a neutral project partner, Fraunhofer IPA conducts comprehensive root-cause analysis using advanced tools like the Leica Absolute Tracker AT960 to record robot positions with submillimeter accuracy. Their approach includes:

Recording the current situation to create a solid database
Calculating special performance indicators to determine system performance
Examining movement characteristics for valuable insights
Investigating both hardware and software components

The team has also developed a specialized closed-loop benchmark that examines the entire robotic cell, including sensor technology and intended processes—going beyond the limited scope of standard ISO 9283 measurements.