activity
20212024
collaborators

7 papers

cs.RO2024

Perception Matters: Enhancing Embodied AI with Uncertainty-Aware Semantic Segmentation

Sai Prasanna, Daniel Honerkamp, Kshitij Sirohi +3

Embodied AI has made significant progress acting in unexplored environments. However, tasks such as object search have largely focused on efficient policy learning. In this work, w…

cs.RO2024

uPLAM: Robust Panoptic Localization and Mapping Leveraging Perception Uncertainties

Kshitij Sirohi, Daniel Büscher, Wolfram Burgard

The availability of a robust map-based localization system is essential for the operation of many autonomously navigating vehicles. Since uncertainty is an inevitable part of perce…

cs.CV2023

EvCenterNet: Uncertainty Estimation for Object Detection using Evidential Learning

Monish R. Nallapareddy, Kshitij Sirohi, Paulo L. J. Drews-Jr +3

Uncertainty estimation is crucial in safety-critical settings such as automated driving as it provides valuable information for several downstream tasks including high-level decisi…

cs.CV2022

Uncertainty-aware LiDAR Panoptic Segmentation

Kshitij Sirohi, Sajad Marvi, Daniel Büscher +1

Modern autonomous systems often rely on LiDAR scanners, in particular for autonomous driving scenarios. In this context, reliable scene understanding is indispensable. Current lear…

cs.CV2022

Uncertainty-aware Panoptic Segmentation

Kshitij Sirohi, Sajad Marvi, Daniel Büscher +1

Reliable scene understanding is indispensable for modern autonomous systems. Current learning-based methods typically try to maximize their performance based on segmentation metric…

cs.RO2021

Robust Monocular Localization in Sparse HD Maps Leveraging Multi-Task Uncertainty Estimation

Kürsat Petek, Kshitij Sirohi, Daniel Büscher +1

Robust localization in dense urban scenarios using a low-cost sensor setup and sparse HD maps is highly relevant for the current advances in autonomous driving, but remains a chall…

cs.CV2021

EfficientLPS: Efficient LiDAR Panoptic Segmentation

Kshitij Sirohi, Rohit Mohan, Daniel Büscher +2

Panoptic segmentation of point clouds is a crucial task that enables autonomous vehicles to comprehend their vicinity using their highly accurate and reliable LiDAR sensors. Existi…