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Publications for: Christopher T. Goodin (Chris)
Peer-Reviewed Journals
Goodin, C., Carrillo, J. T., Monroe, J. G., Carruth, D. W., & Hudson, C. R. (2021). An Analytic Model for Negative Obstacle Detection with Lidar and Numerical Validation Using Physics-Based Simulation. sensors. MDPI. 21(9), 3211. DOI:10.3390/s21093211. [Abstract] [Document] [Document Site]

Dabbiru, L., Goodin, C., Scherer, N., & Carruth, D. W. (2020). LiDAR Data Segmentation in Off-Road Environment Using Convolutional Neural Networks (CNN). SAE International Journal of Advances and Current Practices in Mobility. SAE International. 2, 3288-3292. DOI:https://doi.org/10.4271/2020-01-0696. [Abstract]

Goodin, C., Carruth, D. W., Doude, M., & Hudson, C. R. (2019). Predicting the Influence of Rain on LIDAR in ADAS. Electronics. MDPI. 8(1), 89. DOI:10.3390/electronics8010089. [Abstract] [Document] [Document Site]

Goodin, C., Doude, M., Hudson, C. R., & Carruth, D. W. (2018). Enabling Off-Road Autonomous Navigation-Simulation of LIDAR in Dense Vegetation. Electronics. MDPI. 7(9), 154. DOI:10.3390/electronics7090154. [Abstract] [Document] [Document Site]

Peer-Reviewed Conference Abstracts
Goodin, C., Sharma, S., Doude, M., Carruth, D. W., Dabbiru, L., & Hudson, C. R. (2019). Training of Neural Networks with Automated Labeling of Simulated Sensor Data. SAE Technical Paper 2019-01-0120. Detroit, MI. DOI:10.4271/2019-01-0120. [Abstract] [Document Site]

Peer-Reviewed Conference Papers
Chen, J., Gugssa, M., Yee, J., Goodin, C., & RamDas, A. (2023). Framework for Digital Twin Creation in Off-road Environments from LiDAR Scans. Proc. SPIE 12529, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications. Orlando, FL. DOI:10.1117/12.2663632. [Document Site]

Yu, J., Chen, J., Dabbiru, L., & Goodin, C. (2023). Analysis of LiDAR Configurations on Off-road Semantic Segmentation Performance. Proc. SPIE 12540, Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure. Orlando, FL. DOI:10.1117/12.2663098. [Document Site]

Dabbiru, L., Goodin, C., & Carruth, D. W. (2020). LiDAR Data Segmentation in Off-road Environment Using Convolutional Neural Networks (CNN). SAE International. Detroit, MI. DOI:10.4271/2020-01-0696. [Abstract] [Document Site]

Meadows, W. S., Hudson, C. R., Goodin, C., Dabbiru, L., Powell, B., Doude, M., Carruth, D. W., Islam, M., Ball, J. E., & Tang, B. (2019). Multi-LiDAR Placement, Calibration, Co-registration, and Processing on a Subaru Forester for Off-road Autonomous Vehicles Operations. Proceedings Volume 11009, Autonomous Systems: Sensors, Processing, and Security for Vehicles and Infrastructure 2019. Baltimore, MD. DOI:10.1117/12.2518915. [Abstract] [Document Site]

Hudson, C. R., Goodin, C., Doude, M., & Carruth, D. W. (2018). Analysis of Dual LIDAR Placement for Off-Road Autonomy Using MAVS. 2018 World Symposium on Digital Intelligence for Systems and Machines (DISA). Košice, Slovakia: IEEE. DOI:10.1111/soin.12230. [Abstract] [Document Site]

Durst, P. J., Goodin, C., Anderson, D., & Bethel, C. L. (2017). A Reference Autonomous Mobility Model. 50th Winter Simulation Conference (WSC 2017). Las Vegas, NV.

Monroe, J. G., Doude, M., Haupt, T., Henley, G., Card, A., Mazzola, M., Goodin, C., & Shurin, S. (2017). Thermal Modeling in the Powertrain Analysis and Computational Environment (PACE). 2017 NDIA Ground Vehicle Systems Engineering and Technology Symposium (GVSETS). Detroit, MI. [Abstract] [Document Site]

Davis, J., Bednar, A., Goodin, C., Durst, P., Anderson, D., & Bethel, C. L. (2017). Optimizing Maximally Stable Extremal Region Parameters Using Machine Learning. SPIE Defense + Commercial Sensing Expo - Infrared Technology and Applications XLIII Track. Anaheim, CA: SPIE. [Abstract]