UM Ford Center for Autonomous Vehicles (FCAV)

Preprints/Under Review

S. Kousik, B. Zhang, P. Zhao, and R. Vasudevan, “Safe, Optimal Real-time Trajectory Planning with a Parallel Constrained Bernstein Algorithm." [arXiv]

A. Carlson, R. Vasudevan, and M. Johnson-Roberson, "Shadow Transfer: Single Image Relighting For Urban Road Scenes," Under Review. [arXiv]

P. Hespanhol, M. Porter, R. Vasudevan, and A. Aswani, "Sensor Switching Control Under Attacks Detectable by Finite Sample Dynamic Watermarking Tests," Under Review. [arXiv]

J. Liu, H. Park, M. Johnson-Roberson, and R. Vasudevan, "A Matrix Representation of the Multiple Vehicle Routing Problem for Pickup and Delivery,"arXiv:1809.06746, 2018. [arXiv] [code]

Journal Papers

Y. Yao, E. Atkins, M. Johnson-Roberson, R. Vasudevan, X. Du, “BiTraP: Bi-directional Pedestrian Trajectory Prediction with Multi-modal Goal Estimation," in IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 1463-1470, April 2021. [arXiv][IEEE Xplore][code]

J. Zhang, W. Chen, Y. Wang, R. Vasudevan, M. Johnson-Roberson, “Point Set Voting for Partial Point Cloud Analysis,"in IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 596-603, April 2021. [arXiv]

C. Anderson, R. Vasudevan, and M. Johnson-Roberson, "Off The Beaten Sidewalk: Pedestrian Prediction In Shared Spaces For Autonomous Vehicles," in IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 6892-6899, Oct. 2020. [arXiv][IEEE Xplore][code]

C. Anderson, R. Vasudevan, and M. Johnson-Roberson, "Low Latency Trajectory Predictions for Interaction Aware Highway Driving," in IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 5456-5463, Oct. 2020. [arXiv][IEEE Xplore][code]

S. Kousik, S. Vaskov, F. Bu, M. Johnson-Roberson, and R. Vasudevan, "Bridging the Gap Between Safety and Real-Time Performance in Receding-Horizon Trajectory Design for Mobile Robots," International Journal of Robotics Research, accepted. [arXiv] [videos][code]

M. Porter, P. Hespanhol, A. Aswani, M. Johnson-Roberson, and R. Vasudevan, "Detecting Generalized Replay Attacks via Time-Varying Dynamic Watermarking," IEEE Transactions on Automatic Control, in press. [arXiv]

X. Du, R. Vasudevan, and M. Johnson-Roberson, "Unsupervised Pedestrian Pose Prediction — A deep predictive coding network based approach for autonomous vehicle perception," in IEEE Robotics and Automation Magazine, vol. 27, no. 2, pp. 129-138, June 2020. [IEEE Xplore] [video] [code]

F. Bu, T. Le, X. Du, R. Vasudevan, and M. Johnson-Roberson, "Pedestrian Planar LiDAR Pose (PPLP) Network for Oriented Pedestrian Detection Based on Planar LiDAR and Monocular Images," in IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1626-1633, April 2020. [IEEE Xplore] [video]

P. Zhao, S. Mohan, and R. Vasudevan, “Optimal Control for Nonlinear Hybrid Systems via Convex Relaxations,” IEEE Transactions on Automatic Control, in press. [arXiv]

M. Bartos, H. Park, T. Zhou, B. Kerkez, and R. Vasudevan, "Windshield Wipers on Connected Vehicles Produce High-Accuracy Rainfall Maps," Nature Scientific Reports, vol. 9, no. 170, 2019. [url]

X. Du, R. Vasudevan, and M. Johnson-Roberson, "Bio-LSTM: A Biomechanically Inspired Recurrent Neural Network for 3-D Pedestrian Pose and Gait Prediction," in IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1501-1508, 2019. [arXiv] [IEEE Xplore] [video]

W. Kim, M. Srinivasan Ramanagopal, C. Barto, M.-Y. Yu, K. Rosaen, N. Goumas, R. Vasudevan, and M. Johnson-Roberson, "PedX: Benchmark Dataset for Metric 3-D Pose Estimation of Pedestrians in Complex Urban Intersections," in IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1940-1947, 2019. [arXiv] [IEEE Xplore] [dataset] [code] [video]

M.-Y. Yu, R. Vasudevan, and M. Johnson-Roberson, "Occlusion-Aware Risk Assessment for Autonomous Driving in Urban Environments," in IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 2235-2241, 2019. [arXiv] [IEEE Xplore] [code] [video]

J. Zhang, K. A. Skinner, R. Vasudevan, and M. Johnson-Roberson, "DispSegNet: Leveraging Semantics for End-to-End Learning of Disparity Estimation From Stereo Imagery," in IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1162-1169, 2019. [arXiv] [IEEE Xplore] [code] [video]

A. Carlson, K. A. Skinner, R. Vasudevan, and M. Johnson-Roberson, "Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation for Sim-to-Real Domain Adaptation," in IEEE Robotics and Automation Letters, vol. 4, no. 3, pp. 2431-2438, 2019. [arXiv] [IEEE Xplore] [code]

M. Srinivasan Ramanagopal, C. Anderson, R. Vasudevan, and M. Johnson-Roberson, "Failing to Learn: Autonomously Identifying Perception Failures for Self-driving Cars," in IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 3860-3867, 2018. [arXiv] [IEEE Xplore] [code] [video]

Conference Papers

J. Zhang, M.-Y. Yu, R. Vasudevan, and M. Johnson-Roberson, "Learning Rotation-Invariant Representations of Point Clouds Using Aligned Edge Convolutional Neural Networks," International Conference on 3D Vision 2020 (3DV), 2020. [arXiv]

M. Porter, S. Dey, A. Joshi, P. Hespanhol, A. Aswani, M. Johnson-Roberson, and R. Vasudevan, "Detecting Deception Attacks on Autonomous Vehicles via Linear Time-Varying Dynamic Watermarking," IEEE Conference on Control Technology and Applications, 2020. [arXiv]

P. Holmes, S. Kousik, B. Zhang, D. Raz, C. Barbalata, M. Johnson-Roberson, and R. Vasudevan, "Reachable Sets for Safe, Real-Time Manipulator Trajectory Design," Robotics: Science and Systems, 2020. [arXiv][video]

M. Srinivasan Ramanagopal, Z. Zhang, R. Vasudevan, and M. Johnson-Roberson, ‘‘Pixel-Wise Motion Deblurring of Thermal Videos,” Robotics: Science and Systems, 2020, Accepted. [arXiv][code]

J. Zhang, M. Srinivasan Ramanagopal, R. Vasudevan, and M. Johnson-Roberson, "LiStereo: Generate Dense Depth Maps from LIDAR and Stereo Imagery," IEEE International Conference on Robotics and Automation, 2020, Accepted. [arXiv]

M.-Y. Yu, R. Vasudevan, and M. Johnson-Roberson, "Risk Assessment and Planning with Bidirectional Reachability for Autonomous Driving," IEEE International Conference on Robotics and Automation, 2020, Accepted. [arXiv]

J. Liu, P. Zhao, Z. Gan, M. Johnson-Roberson, and R. Vasudevan, "Leveraging the Template and Anchor Framework for Safe, Online Robotic Gait Design," IEEE International Conference on Robotics and Automation, 2020, Accepted. [arXiv]

S. Kousik, P. Holmes, and R. Vasudevan, "Safe, Aggressive Quadrotor Flight via Reachability-based Trajectory Design," ASME Dynamics Systems and Control Conference, 2019. [arXiv] [video] *Best Student Paper

A. Pakniyat and R. Vasudevan, "A Convex Duality Approach to Optimal Control of Killed Markov Processes," IEEE Conference on Decision and Control, 2019.

M. Monache, J. Sprinkle, R. Vasudevan, and D. Work, "Autonomous Vehicles: From Vehicular Control to Traffic Control," IEEE Conference on Decision and Control, 2019.

C. Anderson, X. Du, R. Vasudevan, and M. Johnson-Roberson, "Stochastic Sampling Simulation for Pedestrian Trajectory Prediction," IEEE/RSJ International Conference on Intelligent Robots and Systems, Macau, China, 2019, pp. 4236-4243. [arXiv][IEEE Xplore] [Code]

S. Vaskov, H. Larson, S. Kousik, M. Johnson-Roberson, and R. Vasudevan, "Not-at-Fault Driving in Traffic: A Reachability-Based Approach," IEEE Intelligent Transportation Systems Conference, Auckland, New Zealand, 2019, pp. 2785-2790. [IEEE Xplore]

S. Vaskov, S. Kousik, H. Larson, F. Bu, J. Ward, S. Worrall, M. Johnson-Roberson, and R. Vasudevan, "Towards Provably Not-at-Fault Control of Autonomous Robots in Arbitrary Dynamic Environments," Robotics: Science and Systems, Freiburg im Breisgau, June 22-26, 2019. [arXiv][url]

S. Vaskov, U. Sharma, S. Kousik, M. Johnson-Roberson, and R. Vasudevan, "Guaranteed Safe Reachability-based Trajectory Design for a High-Fidelity Model of an Autonomous Passenger Vehicle," American Control Conference, Philadelphia, PA, USA, 2019, pp. 705-710. [arXiv] [IEEE Xplore] [video][code]

M. Porter, A. Joshi, P. Hespanhol, A. Aswani, M. Johnson-Roberson, and R. Vasudevan, "Simulation and Real-World Evaluation of Attack Detection Schemes", in American Control Conference, Philadelphia, PA, USA, 2019, pp. 551-558. [arXiv] [IEEE Xplore]

H. Park, J. Liu, M. Johnson-Roberson, and R. Vasudevan, "Robust Environmental Mapping by Mobile Sensor Networks," IEEE International Conference on Robotics and Automation, Brisbane, QLD, 2018, pp. 2395-2402. [arXiv] [IEEE Xplore]

A. Carlson, K. A. Skinner, R. Vasudevan, and M. Johnson-Roberson, "Modeling Camera Effects to Improve Deep Vision for Real and Synthetic Data", European Conference on Computer Vision: Workshop on Visual Learning and Embodied Agents in Simulation Environments, 2018. [arXiv] [url]

P. Hespanhol, M. Porter, R. Vasudevan and A. Aswani, "Statistical Watermarking for Networked Control Systems," Annual American Control Conference (ACC), Milwaukee, WI, 2018, pp. 5467-5472. [arXiv] [IEEE Xplore]

H. Park, M. Johnson-Roberson, and R. Vasudevan, "Robust Dynamic Vehicle Routing for On-Demand Systems Under Light Load," European Nonlinear Dynamics Conference, 2017. [url]

P. Hespanhol, M. Porter, R. Vasudevan and A. Aswani, "Dynamic watermarking for general LTI systems," IEEE 56th Annual Conference on Decision and Control (CDC), Melbourne, VIC, 2017, pp. 1834-1839. [arXiv] [IEEE Xplore]

S. Kousik, S. Vaskov, M. Johnson-Roberson, and R. Vasudevan, "Safe Trajectory Synthesis for Autonomous Driving in Unforeseen Environments," ASME Conference on Dynamics Systems and Control Conference, 2017. [arXiv] [code]

P. Zhao, S. Mohan, and R. Vasudevan, "Control synthesis for nonlinear optimal control via convex relaxations," American Control Conference, Seattle, WA, 2017, pp. 2654-2661. [arXiv] [IEEE Xplore]

M. Johnson-Roberson, C. Barto, R. Mehta, S. N. Sridhar, K. Rosaen and R. Vasudevan, "Driving in the Matrix: Can virtual worlds replace human-generated annotations for real world tasks?," IEEE International Conference on Robotics and Automation, Singapore, 2017, pp. 746-753. [arXiv] [IEEE Xplore] [bibtex] [code] [dataset]