6 citations · 13 across the 14 of their papers we have counts for
5 papers · 1 filter
Propagating State Uncertainty Through Trajectory Forecasting
Boris Ivanovic, Yifeng Lin, Shubham Shrivastava +2
Uncertainty pervades through the modern robotic autonomy stack, with nearly every component (e.g., sensors, detection, classification, tracking, behavior prediction) producing cont…
VR3Dense: Voxel Representation Learning for 3D Object Detection and Monocular Dense Depth Reconstruction
Shubham Shrivastava
3D object detection and dense depth estimation are one of the most vital tasks in autonomous driving. Multiple sensor modalities can jointly attribute towards better robot percepti…
Meta-Regularization by Enforcing Mutual-Exclusiveness
Edwin Pan, Pankaj Rajak, Shubham Shrivastava
Meta-learning models have two objectives. First, they need to be able to make predictions over a range of task distributions while utilizing only a small amount of training data. S…
S-BEV: Semantic Birds-Eye View Representation for Weather and Lighting Invariant 3-DoF Localization
Mokshith Voodarla, Shubham Shrivastava, Sagar Manglani +3
We describe a light-weight, weather and lighting invariant, Semantic Bird's Eye View (S-BEV) signature for vision-based vehicle re-localization. A topological map of S-BEV signatur…
An A* Curriculum Approach to Reinforcement Learning for RGBD Indoor Robot Navigation
Kaushik Balakrishnan, Punarjay Chakravarty, Shubham Shrivastava
Training robots to navigate diverse environments is a challenging problem as it involves the confluence of several different perception tasks such as mapping and localization, foll…