A white paper outlining MIT-PITT-RW’s approach and methods for the Indy Autonomous Challenge.
A paper describing the practical challenges involved in designing our 2018-2019 competition season perception system.
Convenient pytorch based training infrastructure for customized YOLO neural network
We are excited to share our and MIT Han Lab’s work on Point Voxel CNN (PVCNN), the latest LiDAR perception algorithm used by our MIT Driverless cars. Our own Sibo Zhu discusses how this compares to the older designs, the improvements we’ve seen in accuracy and latency, and provides a brief explanation of PVCNN.
Ji Lin, the first author of Temporal Shift Module, gave a tech talk at the group meeting of MIT Driverless.
Recording for the main session of MIT Driverless' End of Summer Showcase on August 28, 2020. MIT Driverless has worked hard all summer to prepare for IAC. Watch to see our progress on architecture, perception, planning and controls!
Recording for the Planning & Controls sub-team's Q&A portion of the MIT Driverless End of Summer Showcase held on August 28, 2020.
To see the other recordings (main session or Q&As), please visit the other videos in this gallery.
Recording for the Perception sub-team's Q&A portion of the MIT Driverless End of Summer Showcase held on August 28, 2020.
To see the other recordings (main session or Q&As), please visit the other videos in our gallery.
Recording for the Architecture sub-team's Q&A portion of the MIT Driverless End of Summer Showcase held on August 28, 2020.
To see the other recordings (main session or Q&As), please visit the other videos in this gallery.
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