# Evaluating the Robot Inclusivity of Buildings Based on Surface Unevenness
## 2 Evaluating Robot Inclusivity  
### Effect of Surface Unvevenness/Vibration on Localization  
For autonomous mobile robots, uneven terrains could cause localization and path planning issues while they are performing their operation [34]. These robots perceive their surroundings using sensors such as Inertial Measurement Units (IMU), LIDARs, cameras, and wheel encoders. Uneven surfaces can introduce errors in the data collected by these sensors, leading to the robot's failure in sensing its location and orientation and its eventual execution of tasks [35] (examples are given in Figure 1). Prominent errors/issues posed to sensing related to localization by unevenness are as follows:* Wheel slippage On uneven terrain, wheel slippage can occur, causing inaccuracies in odometry-based localization methods that rely on precise wheel rotations [36].
* Poor feature detection Accurately perceiving features used for localization, such as landmarks or visual cues, may be impeded due to the vibrations caused to the vision system, making it difficult for the robot to determine its position accurately [37].
* Unpredictable sensor data fluctuation Uneven terrain can cause unpredictable fluctuations in sensor readings, such as from wheel encoders or inertial measurement units (IMUs), leading to inconsistencies in localization through prediction models [38].  
To minimize localization errors in autonomous mobile robots traversing rough terrain, a strategy combining cutting-edge technology and design techniques must be used. Adaptive algorithms and sensor fusion work when effectively combined [15; 39]. State estimation accuracy can be improved using methods like the data filters and fusion to integrate different sensor data. Terrain adaptive algorithms limit the impact of sensor noise after adjusting the robot according to the surface properties of its work environment. Navigation accuracy may be improved even further by designing robots with suspension systems and other devices to manage uneven surfaces. When combined, these tactics enable more dependable and effective robot performance in unpredictable environments. However, these methods may be computationally expensive, complex in design, or require multiple sensors working in tandem. Robot-inclusive design principles as laid out under the DRR approach could be used to mitigate this issue.  
Apart from the localization issues, the continuous exposure of robots to vibrations resulting from uneven surfaces leads to heightened mechanical stress, accelerating the deterioration of various components over time [40]. These vibrations can cause fatigue in critical parts, such as joints and motors, potentially shortening the operational lifespan of the robot. Moreover, repeated exposure to such vibrations may also induce structural damage, compromising the overall performance and reliability of the robot in the long term. Thus, mitigating the effects of surface unevenness becomes essential to preserve the longevity and functionality of the robot in diverse operating environments.  
By assessing the surface unevenness of the deployment site, the proportion of robot performance failures can be reduced through rectification and modification of the environment for robot deployments or by planning paths to avoid poorly inclusive areas. This approach can enhance the productivity of robots by minimizing failures.