Tharun Sethuraman — accepted AI-conference papers

2025

Demonstration-Enhanced Adaptable Multi-Objective Robot Navigation

Jorge de Heuvel, Tharun Sethuraman, Maren Bennewitz

IROS 2025

Preference-Aligned robot navigation in human environments is typically achieved through learning-based approaches, utilizing user feedback or demonstrations for personalization. However, personal preferences are subject to change and might even be context-dependent. Yet traditional reinforcement lea

Cited by 2 Source ↗Scholar ↗

2024

Spatiotemporal Attention Enhances Lidar-Based Robot Navigation in Dynamic Environments

Jorge de Heuvel, Xiangyu Zeng, Weixian Shi, Tharun Sethuraman, Maren Bennewitz

RA-L 2024

Foresighted robot navigation in dynamic indoor environments with cost-efficient hardware necessitates the use of a lightweight yet dependable controller. So inferring the scene dynamics from sensor readings without explicit object tracking is a pivotal aspect of foresighted navigation among pedestri

Cited by 23 Source ↗Scholar ↗