[1] V. Dhiman, A. Kundu, F. Dellaert, and J. J. Corso. Modern MAP inference methods for accurate and faster occupancy grid mapping on higher order factor graphs. In IEEE International Conference on Robotics and Automation (ICRA), 2014. [ bib | http ]
[2] V. Dhiman, J. Ryde, and J. J. Corso. Mutual localization: Two camera relative 6-dof pose estimation from reciprocal fiducial observation. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013. [ bib | .html ]
[3] S. Kumar, V. Dhiman, and J. J. Corso. Learning compositional sparse models of bimodal percepts. In Carla E. Brodley and Peter Stone, editors, Proceedings of AAAI Conference on Artificial Intelligence, pages 366--372. AAAI Press, 2014. [ bib | http ]
[4] J. Ryde, V. Dhiman, and R. Platt. Voxel planes: Rapid visualization and meshification of point cloud ensembles. In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013. [ bib | .pdf ]
[5] V. Dhiman, Q. Tran, J. Corso, and M. Chandraker. A continuous occlusion model for road scene understanding. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 4331--4339, June 2016. [ bib | DOI ]
[6] S. Kumar, V. Dhiman, P. A. Koch, and J. J. Corso. Learning compositional sparse bimodal models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(5):1032--1044, 2018. [ bib | DOI | .pdf ]
[7] V. Dhiman*, S. Banerjee*, B. Griffin, J. M. Siskind, and J. J. Corso. A critical investigation of deep reinforcement learning for navigation. (preprint) ArXiV, abs/1802.02274, 2018. [ bib | arXiv | http ]
[8] V. Dhiman, S. Banerjee, J. M. Siskind, and J. J. Corso. Learning goal-conditioned value functions with one-step path rewards rather than goal-rewards. In (preprint) Open Review, 2019. [ bib | http ]
[9] M. J. Khojasteh*, V. Dhiman*, M. Franceschetti, and N. Atanasov. Probabilistic safety constraints for learned high relative degree system dynamics. In Proceedings of the 2nd Conference on Learning for Dynamics and Control, volume 120 of Proceedings of Machine Learning Research, pages 781--792, The Cloud, 10--11 Jun 2020. PMLR. [ bib | .html | .pdf ]
[10] T. Wang, V. Dhiman, and N. Atanasov. Learning navigation costs from demonstration in partially observable environments. In IEEE International Conference on Robotics and Automation (ICRA), pages 4434--4440, 2020. [ bib | DOI | http ]
[11] T. Wang, V. Dhiman, and N. Atanasov. Learning navigation costs from demonstration with semantic observations. In Learning for Dynamics and Control. PMLR, 2020. [ bib | http ]
[12] J. Bi, V. Dhiman, T. Xiao, and C. Xu. Learning from interventions using hierarchical policies for safe learning. In AAAI Conference on Artificial Intelligence, volume 34, pages 10352--10360, 2020. [ bib | .pdf ]
[13] V. Dhiman*, M. J. Khojasteh*, M. Franceschetti, and N. Atanasov. Control barriers in Bayesian learning of system dynamics. IEEE Transactions on Automatic Control (Under Review), 2020 (Submitted). [ bib | http ]
[14] T. Wang, V. Dhiman, and N. Atanasov. Inverse reinforcement learning for autonomous navigation via differentiable semantic mapping and planning. International Journal of Robotics Research (Under Review), 2020 (Submitted). [ bib | http ]
[15] M. Shan, V. Dhiman, Q. Feng, J. Li, and N. Atanasov. OrcVIO: Object residual constrained Visual-Inertial Odometry. IEEE Transactions on Robotics (Under Review), 2020 (Submitted). [ bib ]

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