IEOR researchers investigate the latest mathematical tools, approaches, and methodologies to make new theoretical discoveries and innovations that touch nearly every industry, making them more efficient and profitable in areas such as supply chain, logistics, manufacturing, data science, energy system, energy systems, robotics, and management.
Seita, Daniel & Jamali, Nawid & Laskey, Michael & Tanwani, Ajay & Berenstein, Ron & Baskaran, Prakash & Iba, Soshi & Canny, John & Goldberg, Kenneth. (2022). Deep Transfer Learning of Pick Points on Fabric for Robot Bed-Making. 10.1007/978-3-030-95459-8_17.
Wilcox, A., Balakrishna, A., Thananjeyan, B., Gonzalez, J.E., and Goldberg, K.. (2022). LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Sparse Reward Iterative Tasks. Proceedings of the 5th Conference on Robot Learning, in Proceedings of Machine Learning Research 164:959-969 Available from https://proceedings.mlr.press/v164/wilcox22a.html.
Simulating Polyculture Farming to Learn Automation Policies for Plant Diversity and Precision Irrigation
Y. Avigal et al., “Simulating Polyculture Farming to Learn Automation Policies for Plant Diversity and Precision Irrigation,” in IEEE Transactions on Automation Science and Engineering, vol. 19, no. 3, pp. 1352-1364, July 2022, doi: 10.1109/TASE.2021.3138995.
Benjamin Insley, Ken Goldberg, Luc Beaulieu, Yunzhi Ma, Stephen McKinley, I-Chow Hsu, J. Adam Cunha, “Comparison of novel shielded nasopharynx applicator designs for intracavitary brachytherapy”, Brachytherapy, Volume 21, Issue 2, 2022, Pages 229-237, ISSN 1538-4721, https://doi.org/10.1016/j.brachy.2021.12.007.
Automating Surgical Peg Transfer: Calibration With Deep Learning Can Exceed Speed, Accuracy, and Consistency of Humans
M. Hwang et al., “Automating Surgical Peg Transfer: Calibration With Deep Learning Can Exceed Speed, Accuracy, and Consistency of Humans,” in IEEE Transactions on Automation Science and Engineering, doi: 10.1109/TASE.2022.3171795.
J. Ichnowski, Y. Avigal, Y. Liu and K. Goldberg, “GOMP-FIT: Grasp-Optimized Motion Planning for Fast Inertial Transport,” 2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 5255-5261, doi: 10.1109/ICRA46639.2022.9812387.