Evaluating the Robot Inclusivity of Buildings Based on Surface Unevenness
Abstract
:1. Introduction
2. Evaluating Robot Inclusivity
2.1. Effect of Surface Unevenness/Vibration on Localization
- Wheel slippageOn uneven terrain, wheel slippage can occur, causing inaccuracies in odometry-based localization methods that rely on precise wheel rotations [36].
- Poor feature detectionAccurately 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 fluctuationUneven 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].
2.2. Measuring Surface Unevenness Using IMU
Algorithm 1 Algorithm for path unevenness index calculation |
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2.3. Determining the Robot Inclusivity Level (RIL)
3. Automated RIL Map Generation
3.1. Robot Platform
3.2. Tagging RIL in a Map
- Collect the data from the IMU, LIDAR, and wheel encoder sensors while performing the zigzag navigation inside the environment.
- Calculate the surface unevenness (U) score from the IMU data. A dedicated node is created to process the data to obtain U in a particular region.
- Convert the recorded U to RIL-SU.
- Tag the RIL-SU onto the corresponding locations of the map generated from the Simultaneous Localization and Mapping (SLAM) system.
- By using the Matplot-lib library system, process all the data to generate the RIL-SU heatmap of the deployed area.
4. Experimental Validation
4.1. Experimental Design
4.2. Test Site 1: Study Area
4.3. Test Site 2: Printing Room
4.4. Test Site 3: Connector Bridge Area
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Borusu, C.S.C.S.; Yeo, M.S.K.; Zeng, Z.; Muthugala, M.A.V.J.; Budig, M.; Elara, M.R.; Wang, Y. Evaluating the Robot Inclusivity of Buildings Based on Surface Unevenness. Appl. Sci. 2024, 14, 7831. https://doi.org/10.3390/app14177831
Borusu CSCS, Yeo MSK, Zeng Z, Muthugala MAVJ, Budig M, Elara MR, Wang Y. Evaluating the Robot Inclusivity of Buildings Based on Surface Unevenness. Applied Sciences. 2024; 14(17):7831. https://doi.org/10.3390/app14177831
Chicago/Turabian StyleBorusu, Charan Satya Chandra Sairam, Matthew S. K. Yeo, Zimou Zeng, M. A. Viraj J. Muthugala, Michael Budig, Mohan Rajesh Elara, and Yixiao Wang. 2024. "Evaluating the Robot Inclusivity of Buildings Based on Surface Unevenness" Applied Sciences 14, no. 17: 7831. https://doi.org/10.3390/app14177831
APA StyleBorusu, C. S. C. S., Yeo, M. S. K., Zeng, Z., Muthugala, M. A. V. J., Budig, M., Elara, M. R., & Wang, Y. (2024). Evaluating the Robot Inclusivity of Buildings Based on Surface Unevenness. Applied Sciences, 14(17), 7831. https://doi.org/10.3390/app14177831